Datasets:

WINGNUS
/

ACL-OCL

	{
	"paper_id": "2022",
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	"date_generated": "2023-01-19T03:29:19.247192Z"
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	"title": "The Human Evaluation Datasheet: A Template for Recording Details of Human Evaluation Experiments in NLP",
	"authors": [
	{
	"first": "Anastasia",
	"middle": [],
	"last": "Shimorina",
	"suffix": "",
	"affiliation": {},
	"email": "[email protected]"
	},
	{
	"first": "Anya",
	"middle": [],
	"last": "Belz",
	"suffix": "",
	"affiliation": {
	"laboratory": "",
	"institution": "University of Aberdeen",
	"location": {
	"country": "UK"
	}
	},
	"email": "[email protected]"
	}
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	"year": "",
	"venue": null,
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	"abstract": "This paper presents the Human Evaluation Datasheet (HEDS), a template for recording the details of individual human evaluation experiments in Natural Language Processing (NLP), and reports on first experience of researchers using HEDS sheets in practice. Originally taking inspiration from seminal papers by Bender and Friedman (2018), Mitchell et al. (2019), and Gebru et al. (2020), HEDS facilitates the recording of properties of human evaluations in sufficient detail, and with sufficient standardisation, to support comparability, meta-evaluation, and reproducibility assessments for human evaluations. These are crucial for scientifically principled evaluation, but the overhead of completing a detailed datasheet is substantial, and we discuss possible ways of addressing this and other issues observed in practice.",
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	"paper_id": "2022",
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	"abstract": [
	{
	"text": "This paper presents the Human Evaluation Datasheet (HEDS), a template for recording the details of individual human evaluation experiments in Natural Language Processing (NLP), and reports on first experience of researchers using HEDS sheets in practice. Originally taking inspiration from seminal papers by Bender and Friedman (2018), Mitchell et al. (2019), and Gebru et al. (2020), HEDS facilitates the recording of properties of human evaluations in sufficient detail, and with sufficient standardisation, to support comparability, meta-evaluation, and reproducibility assessments for human evaluations. These are crucial for scientifically principled evaluation, but the overhead of completing a detailed datasheet is substantial, and we discuss possible ways of addressing this and other issues observed in practice.",
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	"section": "Abstract",
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	"text": "Human evaluation plays a special role in NLP and NLG in particular as it is generally seen as the most reliable form of evaluation (Reiter and Belz, 2009; Novikova et al., 2017; Reiter, 2018) . Comparability and reproducibility of evaluations (both human and automatic) are gaining in recognition and importance across NLP, as the field develops towards scientific maturity. For both reasons, it is of concern that there continues to be little consensus or standard practice across all aspects of human evaluation in NLP. Other efforts are aimed at standardisation of evaluation methods and quality criteria (van der Lee et al., 2021; Gehrmann et al., 2021) . With the Human Evaluation Datasheet (HEDS) we wish to provide simply a way of recording properties of human evaluations in a standard hence comparable form (regardless of the level of standardisation of the deployed methods themselves).",
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	"start": 131,
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	"text": "(Reiter and Belz, 2009;",
	"ref_id": "BIBREF14"
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	"start": 155,
	"end": 177,
	"text": "Novikova et al., 2017;",
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	"start": 178,
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	"text": "Reiter, 2018)",
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	"text": "(van der Lee et al., 2021;",
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	"text": "Gehrmann et al., 2021)",
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	"section": "Introduction",
	"sec_num": "1"
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	"text": "HEDS is a template for recording properties of single human evaluation experiments. It uses multiple-choice questions where possible, for in-creased standardisation and automatic comparability. HEDS is designed to be generally applicable to human evaluations across NLP. It consists of 29 experiment-level questions plus 17 for each quality criterion, available as an online form which also contains explanations and guidance for completing it. The idea is that researchers use completed forms for preregistration of experiments and for archiving their details, to aid in comparability of evaluations across experiments, meta-evaluation of evaluation methods, and reproducibility of results.",
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	"section": "Introduction",
	"sec_num": "1"
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	"text": "Our intention is that HEDS should be suitable for all human evaluation experiments in NLP. Human evaluations in NLP typically get participants to assess system outputs or to interact with systems, but the HEDS sheet also accommodates what we call 'human-authored stand-ins' below, i.e. manually created 'system outputs' (e.g. in a wizard-of-oz scenario or when reference outputs are included in an evaluation) evaluated in a way that can at least in principle be used to evaluate actual system outputs.",
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	"section": "Introduction",
	"sec_num": "1"
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	"text": "The sheet is completed for a single human evaluation experiment by which we mean an experiment that evaluates a single set of directly comparable systems in a single experimental design, but may assess multiple quality criteria. This is the intended meaning when we refer to 'the evaluation experiment' in questions below.",
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	"section": "Introduction",
	"sec_num": "1"
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	"text": "A first version of the datasheet (HEDS 1.0) was reported via a non-archival pre-print . In this paper, we present HEDS in its next revision (v2.0) alongside a summary of what we learnt from observing the datasheet being used in practice since its first publication. We focus discussion in this paper on Questions 4.1.1-4.2.3 (Sections 5 and 6) relating to quality criteria and their operationalisation: these caused some difficulty to users in practice, and were revised more substantively than other questions. The full datasheet is provided in the appendix for reference.",
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	"section": "Relationship to Existing Work",
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	"text": "HEDS directly benefited from several papers and resources. Questions 2.1-2.5 relating to evaluated system, and 4.3.1-4.3.8 relating to response elicitation, are based on Howcroft et al. (2020) , with some significant changes. Questions 4.1.1-4.2.3 relating to quality criteria, and some of the questions about system outputs, evaluators, and experimental design (3.1. 1-3.2.3, 4.3.5, 4.3.6, 4.3.9-4.3.11) are based on Belz et al. (2020) . HEDS was also informed by van der Lee et al. (2019 Lee et al. ( , 2021 and by Gehrmann et al. (2021) 's 1 data card guide.",
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	"start": 170,
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	"text": "Howcroft et al. (2020)",
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	"start": 368,
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	"text": "1-3.2.3, 4.3.5, 4.3.6, 4.3.9-4.3.11)",
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	"text": "Belz et al. (2020)",
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	"text": "Lee et al. (2019",
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	"text": "Lee et al. ( , 2021",
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	"text": "Gehrmann et al. (2021)",
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	"section": "Relationship to Existing Work",
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	"text": "More generally, the original inspiration for creating a 'datasheet' for describing human evaluation experiments of course comes from seminal papers by Bender and Friedman (2018) , Mitchell et al. (2019) and Gebru et al. (2020) .",
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	"start": 151,
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	"text": "Bender and Friedman (2018)",
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	"text": "Mitchell et al. (2019)",
	"ref_id": "BIBREF11"
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	"text": "Gebru et al. (2020)",
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	"section": "Relationship to Existing Work",
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	"text": "HEDS is related to other efforts in the NLP community related to reproducibility and ethics. Different NLP checklists have been introduced in recent years, e.g. the Reproducibility Checklist (Dodge et al., 2019) adopted by many conferences, and the ACL Rolling Review's Responsible NLP checklist. 2 These checklists mainly deal with the recreatability of computational experiments, details of used datasets and models, and risks and limitations of research studies and applications. The focus of HEDS is recording properties of human evaluation experiments, which are not covered by the above checklists.",
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	"text": "(Dodge et al., 2019)",
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	"text": "2",
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	"sec_num": "2"
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	"text": "The Human Evaluation Datasheet package consists of the following three resources:",
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	"section": "HEDS Structure and Resources",
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	"text": "1. The HEDS template: available at https:// forms.gle/MgWiKVu7i5UHeMNQ9; 2. Description and completion guidance: this document;",
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	"section": "HEDS Structure and Resources",
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	"text": "3. Scripts for automatically converting between the HEDS online form and alternative Markdown and LaTeX template formats: available at https://github.com/Shimorina/ human-evaluation-datasheet.",
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	"section": "HEDS Structure and Resources",
	"sec_num": "3"
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	"text": "A collection of completed HEDS datasheets is also available at the HEDS GitHub repository.",
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	"section": "HEDS Structure and Resources",
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	"text": "The full HEDS sheet can be found in Appendix A. In its template form as well as in this paper, HEDS is divided into five sections, addressing topics and containing questions as follows:",
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	"section": "HEDS Structure and Resources",
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	"text": "1. Paper and Resources: HEDS Questions 1.1-1.3, listed in Appendix Section A.1;",
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	"section": "HEDS Structure and Resources",
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	"text": "2. Evaluated System: HEDS Questions 2.1-2.5, Section A.2;",
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	"section": "HEDS Structure and Resources",
	"sec_num": "3"
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	"text": "3. Output Sample, Evaluators and Experimental Design: HEDS Questions 3.1.1-3.3.8, Section A.3;",
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	"section": "HEDS Structure and Resources",
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	"text": "4. Quality Criteria: HEDS Questions 4.1.1-4.3.11, listed in Section 6 of the paper and, for completeness also in Section A.4 in the Appendix-this section is completed separately for each quality criterion used as part of the same evaluation experiment;",
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	"section": "HEDS Structure and Resources",
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	"text": "5. Ethics: HEDS Questions 5.1-5.4, Section A.5.",
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	"section": "HEDS Structure and Resources",
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	"text": "Section A.1 records bibliographic information: link to the paper reporting the evaluation experiment, shared evaluation resources (e.g., a webpage, repository), contact author details.",
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	"section": "HEDS Structure and Resources",
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	"text": "Section A.2 describes information about outputs that are evaluated in the evaluation experiment and how they were produced. For example, it records the task performed by the system, types of system input and output, input and output language.",
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	"section": "HEDS Structure and Resources",
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	"text": "Section A.3 collects information about the evaluated sample (size, selection process, statistical power), the evaluators participating in the experiment, and experimental design (collection method, quality assurance, conditions for evaluators).",
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	"text": "Section A.4 captures information about quality criteria assessed in the human evaluation experiment. We discuss this section in the main body of the paper in Section 6. Section A.5 relates to ethical aspects of the evaluation: approval by ethics committees, and collection of personal and other sensitive data.",
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	"text": "4 Insights from Use of HEDS 1.0 in Practice HEDS 1.0 was used in the 2021 ReproGen Shared Task on Reproducibility of Evaluations in NLG 3 . All shared task participants, as well as the authors of the original papers up for reproduction in Track A, completed the HEDS 1.0 form. Moreover, the HEDS 1.0 sheet was completed another three times outside of the shared task context.",
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	"text": "General feedback from users was that the HEDS 1.0 sheet was for the most part straightforward to complete, but that completion still represented a considerable overhead. This is the general conundrum of initiatives such as HEDS: what is the incentive for researchers to complete the sheet when (i) it is merely good scientific hygiene rather than a component of the work without which it could not be carried out, and (ii) it mainly benefits follow on research rather than the paper it is completed for? Unless it is a requirement for submission to a particular event, or it is generally expected practice, the tendency may always be to avoid the overhead. To address this, we are in the process of preparing a shorter version of the sheet, with the aim of cutting the effort involved in half, for use in contexts where less detail is acceptable.",
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	"text": "We also observed that there were a number of questions in HEDS 1.0 that users found difficult to complete for different reasons. Question 3.1.3 (What is the statistical power of the sample size?) posed difficulties partly because power calculations are a relatively new tool in NLP. We address this in this paper with additional information, and in the future by providing a new resource to support calculation.",
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	"text": "A more fundamental issue was caused by how HEDS 1.0 captured information about quality criteria, and the use of duplicate subsections for multiple quality criteria. We believe that this was due largely to insufficient context, motivation and explanation being provided in the documentation and form about quality criteria and their properties, and we seek to provide the latter in version 2.0 (in this paper as well as in the form).",
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	"text": "Using HEDS as part of the ReproGen shared task demonstrated the utility of having information about original studies and reproduction studies available in the same standard format: it meant it was straightforward for organisers to capture and analyse the similarities and differences between original and reproduction studies, e.g. to identify sources of variation in results for the results report . It also gave participants (authors of reproduction papers) a tool with which to verify whether their reproduction study of human evaluation was the same as the original study in all important respects, at a fine-grained level of detail.",
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	"section": "HEDS Structure and Resources",
	"sec_num": "3"
	},
	{
	"text": "Questions 4.1.1-4.3.11 in HEDS",
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	"section": "Concepts Underlying Quality Criterion",
	"sec_num": "5"
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	"text": "The overall aim of human evaluations in NLP is generally to assess some aspect of the quality of a system or component. Researchers use terms such as Fluency and Informativeness to refer to different aspects of quality. However, as discussed in detail by Howcroft et al. (2020) and Belz et al. (2020) , just because two studies used the same term (e.g. Fluency) it does not mean they evaluated the same aspect of quality. In order to establish what was evaluated, we need to know the term and definition used, but also how it was 'operationalised,' i.e. what was presented to evaluators and how their assessments were recorded. This is why HEDS, picking up from the two publications above, records properties relating to evaluation criteria and their operationalisation separately for each quality criterion. Because within the same experiment different quality criteria are often assessed in similar ways (e.g. using the same rating instrument), this can result in some repetition when completing a HEDS sheet, albeit unfortunately not in predictable ways.",
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	"start": 255,
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	"text": "Howcroft et al. (2020)",
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	"start": 282,
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	"text": "Belz et al. (2020)",
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	"text": "Following Belz et al. (2020) , properties relating to quality criteria and their operationalisation in HEDS fall into three groups: quality criteria, evaluation mode, and experimental design. A quality criterion is a criterion in terms of which the quality of system outputs is assessed, and is in itself entirely agnostic about how it is evaluated. Evaluation modes are properties that need to be specified to turn a quality criterion into an evaluation measure that can be implemented, and are orthogonal to quality criteria, i.e. any given quality criterion can be combined with any mode. Experimental design is the full specification of how to obtain a quantitative or qualitative response value for a given evaluation measure, yielding a fully specified evaluation method. In sum:",
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	"start": 10,
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	"text": "Belz et al. (2020)",
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	"section": "Concepts Underlying Quality Criterion",
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	"text": "\u2022 Quality criterion + evaluation mode = evaluation measure; \u2022 Evaluation measure + experimental design = evaluation method.",
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	"text": "Each of the above concepts is covered by one or more questions in HEDS. Three HEDS questions capture properties of quality criteria in terms of (i) what type of quality is being assessed (Question 4.1.1); (ii) what aspect of the system output is being assessed (Question 4.1.2); and (iii) whether system outputs are assessed in their own right or with reference to some system-internal or systemexternal frame of reference (Question 4.1.3). Three questions capture evaluation mode: (i) subjective vs. objective (Question 4.2.1), (ii) absolute vs. relative (Question 4.2.2), and (iii) intrinsic vs. extrinsic (Question 4.2.3) . Experimental design is covered by Questions 4.3.1-11 (operationalisation of quality criteria assessment), and Questions 3.* (other aspects).",
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	"text": "(Question 4.2.3)",
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	"section": "Concepts Underlying Quality Criterion",
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	"text": "We present, explain and discuss each of the above questions in the following section.",
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	"text": "In this section, we present, verbatim, the questions referred to in the last section relating to properties of quality criteria and their operationalisation. All questions in this section need to be completed once for each quality criterion assessed in the single evaluation experiment that a HEDS sheet is being completed for. E.g. if an evaluation assesses Fluency and Grammaticality, then the questions below need to be filled in, separately, for each. We refer below to 'output' as shorthand for that which is being assessed by evaluators. The latter is most often some form of language output assessed at different lengths (phrase, sentence, document), but it can also be a more complete form of system behaviour (e.g. language displayed along with audio and/or visual elements, on interfaces, etc.). It is in this more general sense that we intend the term 'output' to be understood in the present context. 6.1 Quality criterion properties (Questions 4.1.1-4.1.3)",
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	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
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	"text": "Questions 4.1.1-4.1.3 capture the aspect of quality that is assessed by a given quality criterion, in terms of three orthogonal properties. They help determine whether or not the same aspect of quality is being evaluated in different evaluation experiments. The three properties characterise quality criteria in terms of (i) what type of quality is being assessed; (ii) what aspect of the system output is being assessed; and (iii) whether system outputs are assessed in their own right or with reference to some system-internal or system-external frame of reference. For full explanations see Belz et al. (2020) .",
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	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
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	"text": "Note that if NLP had a generally accepted standard set of quality criteria with common names, definitions and operationalisations, then most of the questions in this section could be replaced by a much smaller set capturing criterion name and operationalising techniques. The reason there are so many questions is precisely because we do not have such a standard nomenclature.",
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	"text": "Question 4.1.1: What type of quality is assessed by the quality criterion?",
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	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
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	},
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	"text": "Multiple-choice options (select one):",
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	"text": "\u2022 Correctness: Select this option if it is possible to state, generally for all outputs, the conditions under which outputs are maximally correct (hence of maximal quality). E.g. for Grammaticality, 4 outputs are (maximally) correct if they contain no grammatical errors; for Semantic Completeness, outputs are correct if they express all the content in the input.",
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	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
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	"text": "\u2022 Goodness: Select this option if, in contrast to correctness criteria, there is no single, general mechanism for deciding when outputs are maximally good, only for deciding for any two outputs which is better and which is worse. E.g. for Fluency, even if outputs contain no disfluencies, there may be other ways in which any given output could be more fluent.",
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	"text": "\u2022 Feature: Choose this option if, in terms of property X captured by the criterion, outputs are not generally better if they are more X, but instead, depending on evaluation context, more X may be either better or worse. E.g. for Specificity, outputs can be more specific or less specific, but it's not the case that outputs are, in the general case, better when they are more specific.",
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	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
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	{
	"text": "Question 4.1.2: Which aspect of system outputs is assessed by the quality criterion?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Form of output: Choose this option if the criterion assesses the form of outputs alone, e.g. Grammaticality is only about the form, a sentence can be grammatical yet be wrong or nonsensical in terms of content.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Content of output: Select this option if the criterion assesses the content/meaning of the output alone, e.g. Meaning Preservation only assesses content; two sentences can be considered to have the same meaning, but differ in form.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Both form and content of output: Choose this option if the criterion assesses outputs as a whole, not just form or just content. E.g. Coherence is a property of outputs as a whole, either form or meaning can detract from it. Inherently extrinsic criteria such as Usefulness or Task Completion also fall in this category.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Question 4.1.3: Is each output assessed for quality in its own right, or with reference to a system-internal or external frame of reference?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Quality of output in its own right: Select this option if output quality is assessed without referring to anything other than the output itself, i.e. no system-internal or external frame of reference. E.g. Poeticness is assessed by considering (just) the output and how poetic it is.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Quality of output relative to the input: Choose this option if output quality is assessed relative to the input. E.g. Answerability is the degree to which the output question can be answered from information in the input.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Quality of output relative to a system-external frame of reference: Choose this option if output quality is assessed with reference to systemexternal information, such as a knowledge base, a person's individual writing style, or the performance of an embedding system. E.g. Factual Accuracy assesses outputs relative to a source of real-world knowledge. Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Objective: Choose this option if the evaluation uses objective assessment, e.g. any automatically counted or otherwise quantified measurements such as mouse-clicks, occurrences in text, etc. Repeated assessments of the same output with an objective-mode evaluation method always yield the same score/result.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Subjective: Choose this option in all other cases.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Subjective assessments involve ratings, opinions and preferences by evaluators. Some criteria lend themselves more readily to subjective assessments, e.g. Friendliness of a conversational agent, but an objective measure e.g. based on lexical markers is also conceivable. Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Absolute: Select this option if evaluators are shown outputs from a single system during each individual assessment.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Relative: Choose this option if evaluators are shown outputs from multiple systems at the same time during assessments, typically ranking or preference-judging them. Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Intrinsic: Choose this option if quality of outputs is assessed without considering their effect on something external to the system, e.g. the performance of an embedding system or of a user at a task.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Extrinsic: Choose this option if quality of outputs is assessed in terms of their effect on something external to the system such as the performance of an embedding system or of a user at a task.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "6.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "The questions in this section concern response elicitation, by which we mean how the ratings or other measurements that represent assessments for the quality criterion in question are obtained, What to enter in the text box: The number of different response values for this quality criterion. E.g. for a 5-point Likert scale, the size to enter is 5. For two-way forced-choice preference judgments, it is 2; if there's also a no-preference option, enter 3. For a slider that is mapped to 100 different values for the purpose of recording assessments, the size to enter is 100. If no rating instrument is used (e.g. when evaluation gathers post-edits or qualitative feedback only), enter 'N/A'. What to enter in the text box: list, or give the range of, the possible values of the rating instrument. The list or range should be of the size specified in Question 4.3.3. If there are too many to list, use a range. E.g. for two-way forced-choice preference judgments, the list entered might be A better, B better; if there's also a no-preference option, the list might be A better, B better, neither. For a slider that is mapped to 100 different values for the purpose of recording assessments, the range 1-100 might be entered. If no rating instrument is used (e.g. when evaluation gathers post-edits or qualitative feedback only), enter 'N/A'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Question 4.3.5: How is the scale or other rating instrument presented to evaluators? If none match, select 'Other' and describe.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Multiple-choice options: choose this option if evaluators select exactly one of multiple options.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Check-boxes: choose this option if evaluators select any number of options from multiple given options.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Slider: choose this option if evaluators move a pointer on a slider scale to the position corresponding to their assessment.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 N/A (there is no rating instrument): choose this option if there is no rating instrument.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Other (please specify): choose this option if there is a rating instrument, but none of the above adequately describe the way you present it to evaluators. Use the text box to describe the rating instrument and link to a screenshot.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Question 4.3.6: If there is no rating instrument, describe briefly what task the evaluators perform (e.g. ranking multiple outputs, finding information, playing a game, etc.), and what information is recorded. Enter 'N/A' if there is a rating instrument.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "What to enter in the text box: If (and only if) there is no rating instrument, i.e. you entered 'N/A' for Questions 4.3.3-4.3.5, describe the task evaluators perform in this space. Otherwise, here enter 'N/A' if there is a rating instrument.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Question 4.3.7: What is the verbatim question, prompt or instruction given to evaluators (visible to them during each individual assessment)?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "What to enter in the text box: Copy and paste the verbatim text that evaluators see during each assessment, that is intended to convey the evaluation task to them. E.g. Which of these texts do you prefer?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Or Make any corrections to this text that you think are necessary in order to improve it to the point where you would be happy to provide it to a client. \u2022 (dis)agreement with quality statement: Participants specify the degree to which they agree with a given quality statement by indicating their agreement on a rating instrument. The rating instrument is labelled with degrees of agreement and can additionally have numerical labels. E.g. This text is fluent -1=strongly disagree...5=strongly agree.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 direct quality estimation: Participants are asked to provide a rating using a rating instrument, which typically (but not always) mentions the quality criterion explicitly. E.g. How fluent is this text? -1=not at all fluent...5=very fluent.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 relative quality estimation (including ranking):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Participants evaluate two or more items in terms of which is better. E.g. Rank these texts in terms of fluency; Which of these texts is more fluent?; Which of these items do you prefer?.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 counting occurrences in text: Evaluators are asked to count how many times some type of phenomenon occurs, e.g. the number of facts contained in the output that are inconsistent with the input.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 qualitative feedback (e.g. via comments entered in a text box): Typically, these are responses to open-ended questions in a survey or interview.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 evaluation through post-editing/annotation:",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Choose this option if the evaluators' task consists of editing or inserting annotations in text. E.g. evaluators may perform error correction and edits are then automatically measured to yield a numerical score.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 output classification or labelling: Choose this option if evaluators assign outputs to categories. E.g. What is the overall sentiment of this piece of text? -Positive/neutral/negative.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 user-text interaction measurements: choose this option if participants in the evaluation experiment interact with a text in some way, and measurements are taken of their interaction. E.g. reading speed, eye movement tracking, comprehension questions, etc. Excludes situations where participants are given a task to solve and their performance is measured which comes under the next option.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 task performance measurements: choose this option if participants in the evaluation experiment are given a task to perform, and measure-ments are taken of their performance at the task. E.g. task is finding information, and task performance measurement is task completion speed and success rate.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 user-system interaction measurements: choose this option if participants in the evaluation experiment interact with a system in some way, while measurements are taken of their interaction. E.g. duration of interaction, hyperlinks followed, number of likes, or completed sales.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "\u2022 Other (please specify): Use the text box to describe the form of response elicitation used in assessing the quality criterion if it doesn't fall in any of the above categories.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Question 4.3.9: How are raw responses from participants aggregated or otherwise processed to obtain reported scores for this quality criterion? State if no scores reported.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "What to enter in the text box: normally a set of separate assessments is collected from evaluators and is converted to the results as reported. Describe here the method(s) used in the conversion(s). E.g. macro-averages or micro-averages are computed from numerical scores to provide summary, persystem results.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "Question 4.3.10: Method(s) used for determining effect size and significance of findings for this quality criterion.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "What to enter in the text box: A list of methods used for calculating the effect size and significance of any results, both as reported in the paper given in Question 1.1, for this quality criterion. If none calculated, state 'None'. What to enter in the text box: the methods used to compute, and results obtained from, any measures of inter-annotator and intra-annotator agreement obtained for the quality criterion.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "HEDS Questions about Properties of Quality Criteria and their Operationalisation",
	"sec_num": "6"
	},
	{
	"text": "In this paper we have presented the Human Evaluation Datasheet (HEDS), intended as a way of recording properties of human evaluations in NLP in a sufficiently standardised way to support comparability between evaluation experiments, metaevaluation of evaluation methods, and reproducibility assessments of evaluation results. We have reported insights from observing HEDS 1.0 being used in practice, and have described improvements we have made in response to these insights. In particular, we have provided additional context, motivation and explanation to the HEDS questions relating to evaluation criteria assessed in evaluation experiments and their operationalisation. Moreover, we are currently developing a shorter version of HEDS, a version with reduced effort for use in certain contexts.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "We view HEDS as continuing to develop in response to feedback received and insights gathered through use in practice. We continue to welcome feedback on any aspect of HEDS, and hope the growing repository of completed sheets will prove useful for future comparisons, meta-evaluation and reproducibility assessments, as demonstrated in the ReproGen shared task. What to enter in the text box: a link to an online copy of the main reference for the human evaluation experiment, identifying which of the experiments the form is being completed for if there are several. If the experiment hasn't been run yet, and the form is being completed for the purpose of submitting it for preregistration, simply enter 'for preregistration'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Question 1.2: Link to website providing resources used in the evaluation experiment (e.g. system outputs, evaluation tools, etc.). If there isn't one, enter 'N/A'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "What to enter in the text box: link(s) to any resources used in the evaluation experiment, such as system outputs, evaluation tools, etc. If there aren't any publicly shared resources (yet), enter 'N/A'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Question 1.3: Name, affiliation and email address of person completing this sheet, and of contact author if different.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "What to enter in the text box: names, affiliations and email addresses as appropriate.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "A.2 System Questions 2.1-2.5",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Questions 2.1-2.5 record information about the system(s) (or human-authored stand-ins) whose outputs are evaluated in the Evaluation experiment that this sheet is being completed for.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "The input, output, and task questions in this section are closely interrelated: the value for one partially determines the others, as indicated for some combinations in Question 2.3.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Question 2.1: What type of input do the evaluated system(s) take? Select all that apply. If none match, select 'Other' and describe.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Describe the type of input, where input refers to the representations and/or data structures shared by all evaluated systems.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "This question is about input type, regardless of number. E.g. if the input is a set of documents, you would still select text: document below.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Check-box options (select all that apply):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 raw/structured data: numerical, symbolic, and other data, possibly structured into trees, graphs, graphical models, etc. May be the input e.g. to Referring Expression Generation (REG), endto-end text generation, etc. NB: excludes linguistic structures. \u25a1 shallow linguistic representation (SLR): any of a variety of shallow, syntactic representations, e.g. Universal Dependency (UD) structures; typically the input to surface realisation.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: subsentential unit of text: a unit of text shorter than a sentence, e.g. Referring Expressions (REs), verb phrase, text fragment of any length; includes titles/headlines.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: sentence: a single sentence (or set of sentences).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: multiple sentences: a sequence of multiple sentences, without any document structure (or a set of such sequences).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: document: a text with document structure, such as a title, paragraph breaks or sections, e.g. a set of news reports for summarisation.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: dialogue: a dialogue of any length, excluding a single turn which would come under one of the other text types.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: other: input is text but doesn't match any of the above text:* categories.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 speech: a recording of speech.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 visual: an image or video.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 multi-modal: catch-all value for any combination of data and/or linguistic representation and/or visual data etc.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 control feature: a feature or parameter specifically present to control a property of the output text, e.g. positive stance, formality, author style.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 no input (human generation): human generation 6 , therefore no system inputs.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 other (please specify): if input is none of the above, choose this option and describe it.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Question 2.2: What type of output do the evaluated system(s) generate? Select all that apply. If none match, select 'Other' and describe.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Describe the type of output, where output refers to the representations and/or data structures shared by all evaluated systems. This question is about output type, regardless of number. E.g. if the output is a set of documents, you would still select text: document below.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Note that the options for outputs are the same as for inputs except that the no input (human generation) option is replaced with human-generated 'outputs', and the control feature option is removed.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Check-box options (select all that apply): \u25a1 raw/structured data: numerical, symbolic, and other data, possibly structured into trees, graphs, graphical models, etc. May be the input e.g. to Referring Expression Generation (REG), endto-end text generation, etc. NB: excludes linguistic structures. \u25a1 shallow linguistic representation (SLR): any of a variety of shallow, syntactic representations, e.g. Universal Dependency (UD) structures; typically the input to surface realisation.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: subsentential unit of text: a unit of text shorter than a sentence, e.g. Referring Expressions (REs), verb phrase, text fragment of any length; includes titles/headlines.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: sentence: a single sentence (or set of sentences).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: multiple sentences: a sequence of multiple sentences, without any document structure (or a set of such sequences).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: document: a text with document structure, such as a title, paragraph breaks or sections, e.g. a set of news reports for summarisation.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: dialogue: a dialogue of any length, excluding a single turn which would come under one of the other text types.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 text: other: select if output is text but doesn't match any of the above text:* categories.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 speech: a recording of speech.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 visual: an image or video.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 multi-modal: catch-all value for any combination of data and/or linguistic representation and/or visual data etc.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 human-generated 'outputs': manually created stand-ins exemplifying outputs. 6",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 other (please specify): if output is none of the above, choose this option and describe it.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Question 2.3: How would you describe the task that the evaluated system(s) perform in mapping the inputs in Q2.1 to the outputs in Q2.2? Occasionally, more than one of the options below may apply. If none match, select 'Other' and describe. This field records the task performed by the system(s) being evaluated. This is independent of the application domain (financial reporting, weather forecasting, etc.), or the specific method (rulebased, neural, etc.) implemented in the system. We indicate mutual constraints between inputs, outputs and task for some of the options below.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Check-box options (select all that apply):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 content selection/determination: selecting the specific content that will be expressed in the generated text from a representation of possible content. This could be attribute selection for REG (without the surface realisation step). Note that the output here is not text.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 content ordering/structuring: assigning an order and/or structure to content to be included in generated text. Note that the output here is not text.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 aggregation: converting inputs (typically deep linguistic representations or shallow linguistic representations) in some way in order to reduce redundancy (e.g. representations for 'they like swimming', 'they like running' \u2192 representation for 'they like swimming and running').",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 referring expression generation: generating text to refer to a given referent, typically represented in the input as a set of attributes or a linguistic representation.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 lexicalisation: associating (parts of) an input representation with specific lexical items to be used in their realisation.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 deep generation: one-step text generation from raw/structured data or deep linguistic representations. One-step means that no intermediate representations are passed from one independently run module to another.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 surface realisation (SLR to text): one-step text generation from shallow linguistic representations. One-step means that no intermediate representations are passed from one independently run module to another.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 feature-controlled text generation: generation of text that varies along specific dimensions where the variation is controlled via control features specified as part of the input. Input is a non-textual representation (for featurecontrolled text-to-text generation select the matching text-to-text task).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 data-to-text generation: generation from raw/structured data which may or may not include some amount of content selection as part of the generation process. Output is likely to be text:* or multi-modal.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 dialogue turn generation: generating a dialogue turn (can be a greeting or closing) from a representation of dialogue state and/or last turn(s), etc.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 question generation: generation of questions from given input text and/or knowledge base such that the question can be answered from the input.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 question answering: input is a question plus optionally a set of reference texts and/or knowledge base, and the output is the answer to the question.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 paraphrasing/lossless simplification: text-totext generation where the aim is to preserve the meaning of the input while changing its wording. This can include the aim of changing the text on a given dimension, e.g. making it simpler, changing its stance or sentiment, etc., which may be controllable via input features. Note that this task type includes meaningpreserving text simplification (non-meaning preserving simplification comes under compression/lossy simplification below).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 compression/lossy simplification: text-to-text generation that has the aim to generate a shorter, or shorter and simpler, version of the input text. This will normally affect meaning to some extent, but as a side effect, rather than the primary aim, as is the case in summarisation.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 machine translation: translating text in a source language to text in a target language while maximally preserving the meaning.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 summarisation (text-to-text): output is an extractive or abstractive summary of the important/relevant/salient content of the input document(s).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 end-to-end text generation: use this option if the single system task corresponds to more than one of tasks above, implemented either as separate modules pipelined together, or as one-step generation, other than deep generation and surface realisation.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 image/video description: input includes visual, and the output describes it in some way.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 post-editing/correction: system edits and/or corrects the input text (typically itself the textual output from another system) to yield an improved version of the text.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "\u25a1 other (please specify): if task is none of the above, choose this option and describe it. This field records the language(s) of the inputs accepted by the system(s) being evaluated.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "What to enter in the text box: any language name(s) that apply, mapped to standardised full language names in ISO 639-1 7 . E.g. English, Herero, Hindi. If no language is accepted as (part of) the input, enter 'N/A'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "Question 2.5: Output Language(s), or 'N/A'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "This field records the language(s) of the outputs generated by the system(s) being evaluated.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "What to enter in the text box: any language name(s) that apply, mapped to standardised full language names in ISO 639-1 (2019) 7 . E.g. English, Herero, Hindi. If no language is generated, enter 'N/A'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "Conclusion",
	"sec_num": "7"
	},
	{
	"text": "A.3.1 Sample of system outputs (or human-authored stand-ins) evaluated (Questions 3.1.1-3.1.3)",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Questions 3.1.1-3.1.3 record information about the size of the sample of outputs (or human-authored stand-ins) evaluated per system, how the sample was selected, and what its statistical power is.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Question 3.1.1: How many system outputs (or other evaluation items) are evaluated per system in the evaluation experiment? Answer should be an integer.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: The number of system outputs (or other evaluation items) that are evaluated per system by at least one evaluator in the experiment, as an integer.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Question 3.1.2: How are system outputs (or other evaluation items) selected for inclusion in the evaluation experiment? If none match, select 'Other' and describe.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 by an automatic random process from a larger set: outputs were selected for inclusion in the experiment by a script using a pseudo-random number generator; don't use this option if the script selects every nth output (which is not random).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 by an automatic random process but using stratified sampling over given properties: use this option if selection was by a random script as above, but with added constraints ensuring that the sample is representative of the set of outputs it was selected from, in terms of given properties, such as sentence length, positive/negative stance, etc.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 by manual, arbitrary selection: output sample was selected by hand, or automatically from a manually compiled list, without a specific selection criterion.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 by manual selection aimed at achieving balance or variety relative to given properties: selection by hand as above, but with specific selection criteria, e.g. same number of outputs from each time period.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 Other (please specify): if selection method is none of the above, choose this option and describe it.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Question 3.1.3: What is the statistical power of the sample size?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: The results of a statistical power calculation on the output sample: provide numerical results and a link to the script used (or another way of identifying the script). See, e.g., Card et al. (2020) ; Howcroft and Rieser (2021 \u25a1 not paid: participants were not given compensation of any kind.",
	"cite_spans": [
	{
	"start": 211,
	"end": 229,
	"text": "Card et al. (2020)",
	"ref_id": "BIBREF4"
	},
	{
	"start": 232,
	"end": 257,
	"text": "Howcroft and Rieser (2021",
	"ref_id": "BIBREF9"
	}
	],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 previously known to authors: (one of the) researchers running the experiment knew some or all of the participants before recruiting them for the experiment.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 not previously known to authors: none of the researchers running the experiment knew any of the participants before recruiting them for the experiment.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 evaluators include one or more of the authors: one or more researchers running the experiment was among the participants.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 evaluators do not include any of the authors: none of the researchers running the experiment were among the participants.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 Other (fewer than 4 of the above apply): we believe you should be able to tick 4 options of the above. If that's not the case, use this box to explain. What to enter in the text box: Use this space to describe any training evaluators were given as part of the experiment to prepare them for the evaluation task, including any practice evaluations they did. This includes any introductory explanations they're given, e.g. on the start page of an online evaluation tool.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Question 3.2.5: What other characteristics do the evaluators have, known either because these were qualifying criteria, or from information gathered as part of the evaluation?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: Use this space to list any characteristics not covered in previous questions that the evaluators are known to have, either because evaluators were selected on the basis of a characteristic, or because information about a characteristic was collected as part of the evaluation. \u25a1 evaluators are excluded if they fail quality checks (often or badly enough): there are conditions under which evaluations produced by participants are not included in the final results due to quality issues.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 some evaluations are excluded because of failed quality checks: there are conditions under which some (but not all) of the evaluations produced by some participants are not included in the final results due to quality issues.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 none of the above: tick this box if none of the above apply.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 Other (please specify): use this box to describe any other quality assurance methods used during or after evaluations, and to provide additional details for any of the options selected above.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Question 3.3.4: What do evaluators see when carrying out evaluations? Link to screenshot(s) and/or describe the evaluation interface(s).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: Use this space to describe the interface, paper form, etc. that evaluators see when they carry out the evaluation. Link to a screenshot/copy if possible. If there is a separate introductory interface/page, include it under Question 3.2.4.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "3.3.5: How free are evaluators regarding when and how quickly to carry out evaluations? Select all that apply. In all cases, provide details in the text box under 'Other'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Check-box options (select all that apply):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 evaluators have to complete each individual assessment within a set time: evaluators are timed while carrying out each assessment and cannot complete the assessment once time has run out.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 evaluators have to complete the whole evaluation in one sitting: partial progress cannot be saved and the evaluation returned to on a later occasion.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 neither of the above: Choose this option if neither of the above are the case in the experiment.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 Other (please specify): Use this space to describe any other way in which time taken or number of sessions used by evaluators is controlled in the experiment, and to provide additional details for any of the options selected above.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "3.3.6: Are evaluators told they can ask questions about the evaluation and/or provide feedback? Select all that apply. In all cases, provide details in the text box under 'Other'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Check-box options (select all that apply):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 evaluators are told they can ask any questions during/after receiving initial training/instructions, and before the start of the evaluation: evaluators are told explicitly that they can ask questions about the evaluation experiment before starting on their assessments, either during or after training.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 evaluators are told they can ask any questions during the evaluation: evaluators are told explicitly that they can ask questions about the evaluation experiment during their assessments.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 evaluators are asked for feedback and/or comments after the evaluation, e.g. via an exit questionnaire or a comment box: evaluators are explicitly asked to provide feedback and/or comments about the experiment after their assessments, either verbally or in written form.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 None of the above: Choose this option if none of the above are the case in the experiment.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u25a1 Other (please specify): use this space to describe any other ways you provide for evaluators to ask questions or provide feedback.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "3.3.7: What are the experimental conditions in which evaluators carry out the evaluations? If none match, select 'Other' and describe.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 evaluation carried out by evaluators at a place of their own choosing, e.g. online, using a paper form, etc.: evaluators are given access to the tool or form specified in Question 3.3.2, and subsequently choose where to carry out their evaluations.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 evaluation carried out in a lab, and conditions are the same for each evaluator: evaluations are carried out in a lab, and conditions in which evaluations are carried out are controlled to be the same, i.e. the different evaluators all carry out the evaluations in identical conditions of quietness, same type of computer, same room, etc. Note we're not after very fine-grained differences here, such as time of day or temperature, but the line is difficult to draw, so some judgment is involved here.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 evaluation carried out in a lab, and conditions vary for different evaluators: choose this option if evaluations are carried out in a lab, but the preceding option does not apply, i.e. conditions in which evaluations are carried out are not controlled to be the same.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 evaluation carried out in a real-life situation, and conditions are the same for each evaluator: evaluations are carried out in a real-life situation, i.e. one that would occur whether or not the evaluation was carried out (e.g. evaluating a dialogue system deployed in a live chat function on a website), and conditions in which evaluations are carried out are controlled to be the same.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 evaluation carried out in a real-life situation, and conditions vary for different evaluators: choose this option if evaluations are carried out in a real-life situation, but the preceding option does not apply, i.e. conditions in which evaluations are carried out are not controlled to be the same.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 evaluation carried out outside of the lab, in a situation designed to resemble a real-life situation, and conditions are the same for each evaluator: evaluations are carried out outside of the lab, in a situation intentionally similar to a real-life situation (but not actually a real-life situation), e.g. user-testing a navigation system where the destination is part of the evaluation design, rather than chosen by the user. Conditions in which evaluations are carried out are controlled to be the same.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 evaluation carried out outside of the lab, in a situation designed to resemble a real-life situation, and conditions vary for different evaluators: choose this option if evaluations are carried out outside of the lab, in a situation intentionally similar to a real-life situation, but the preceding option does not apply, i.e. conditions in which evaluations are carried out are not controlled to be the same.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "\u2022 Other (please specify): Use this space to provide additional, or alternative, information about the conditions in which evaluators carry out assessments, not covered by the options above.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "3.3.8: Unless the evaluation is carried out at a place of the evaluators' own choosing, briefly describe the (range of different) conditions in which evaluators carry out the evaluations.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: use this space to describe the variations in the conditions in which evaluators carry out the evaluation, for both situations where those variations are controlled, and situations where they are not controlled.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.3 Questions about Output Sample, Evaluators, Experimental Design",
	"sec_num": null
	},
	{
	"text": "Questions in this section collect information about the nth quality criterion assessed in the single human evaluation experiment that this sheet is being completed for.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "A.4.1 Quality criterion properties (Questions 4.1.1-4.1.3)",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Questions 4.1.1-4.1.3 capture the aspect of quality that is assessed by a given quality criterion in terms of three orthogonal properties. They help determine whether or not the same aspect of quality is being evaluated in different evaluation experiments. The three properties characterise quality criteria in terms of (i) what type of quality is being assessed; (ii) what aspect of the system output is being assessed; and (iii) whether system outputs are assessed in their own right or with reference to some system-internal or system-external frame of reference. For full explanations see Belz et al. (2020) .",
	"cite_spans": [
	{
	"start": 593,
	"end": 611,
	"text": "Belz et al. (2020)",
	"ref_id": "BIBREF1"
	}
	],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Question 4.1.1: What type of quality is assessed by the quality criterion?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Correctness: Select this option if it is possible to state, generally for all outputs, the conditions under which outputs are maximally correct (hence of maximal quality). E.g. for Grammaticality, 8 outputs are (maximally) correct if they contain no grammatical errors; for Semantic Completeness, outputs are correct if they express all the content in the input.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Goodness: Select this option if, in contrast to correctness criteria, there is no single, general mechanism for deciding when outputs are maximally good, only for deciding for any two outputs which is better and which is worse. E.g. for Fluency, even if outputs contain no disfluencies, there may be other ways in which any given output could be more fluent.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Feature: Choose this option if, in terms of property X captured by the criterion, outputs are not generally better if they are more X, but instead, depending on evaluation context, more X may be either better or worse. E.g. for Specificity, outputs can be more specific or less specific, but it's not the case that outputs are, in the general case, better when they are more specific.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Question 4.1.2: Which aspect of system outputs is assessed by the quality criterion?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Form of output: Choose this option if the criterion assesses the form of outputs alone, e.g. Grammaticality is only about the form, a sentence can be grammatical yet be wrong or nonsensical in terms of content.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Content of output: Select this option if the criterion assesses the content/meaning of the output alone, e.g. Meaning Preservation only assesses content; two sentences can be considered to have the same meaning, but differ in form.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Both form and content of output: Choose this option if the criterion assesses outputs as a whole, not just form or just content. E.g. Coherence is a property of outputs as a whole, either form or meaning can detract from it. Inherently extrinsic criteria such as Usefulness or Task Completion also fall in this category.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Question 4.1.3: Is each output assessed for quality in its own right, or with reference to a system-internal or external frame of reference?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Quality of output in its own right: Select this option if output quality is assessed without referring to anything other than the output itself, i.e. no system-internal or external frame of reference. E.g. Poeticness is assessed by considering (just) the output and how poetic it is.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Quality of output relative to the input: Choose this option if output quality is assessed relative to the input. E.g. Answerability is the degree to which the output question can be answered from information in the input.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Quality of output relative to a system-external frame of reference: Choose this option if output quality is assessed with reference to systemexternal information, such as a knowledge base, a person's individual writing style, or the performance of an embedding system. E.g. Factual Accuracy assesses outputs relative to a source of real-world knowledge.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "A.4.2 Evaluation mode properties (Questions 4.2.1-4.2.3)",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Questions 4.2.1-4.2.3 record properties that are orthogonal to quality criteria (covered by questions in the preceding section), i.e. any given quality criterion can in principle be combined with any of the modes (although some combinations are more common than others). Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Objective: Choose this option if the evaluation uses objective assessment, e.g. any automatically counted or otherwise quantified measurements such as mouse-clicks, occurrences in text, etc. Repeated assessments of the same output with an objective-mode evaluation method always yield the same score/result.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Subjective: Choose this option in all other cases.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Subjective assessments involve ratings, opinions and preferences by evaluators. Some criteria lend themselves more readily to subjective assessments, e.g. Friendliness of a conversational agent, but an objective measure e.g. based on lexical markers is also conceivable.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Question 4.2.2: Are outputs assessed in absolute or relative terms?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Absolute: Select this option if evaluators are shown outputs from a single system during each individual assessment.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Relative: Choose this option if evaluators are shown outputs from multiple systems at the same time during assessments, typically ranking or preference-judging them.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Question 4.2.3: Is the evaluation intrinsic or extrinsic?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Intrinsic: Choose this option if quality of outputs is assessed without considering their effect on something external to the system, e.g. the performance of an embedding system or of a user at a task.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "\u2022 Extrinsic: Choose this option if quality of outputs is assessed in terms of their effect on something external to the system such as the performance of an embedding system or of a user at a task.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4 Quality Criterion n -Definition and Operationalisation",
	"sec_num": null
	},
	{
	"text": "The questions in this section concern response elicitation, by which we mean how the ratings or other measurements that represent assessments for the quality criterion in question are obtained, What to enter in the text box: The number of different response values for this quality criterion. E.g. for a 5-point Likert scale, the size to enter is 5. For two-way forced-choice preference judgments, it is 2; if there's also a no-preference option, enter 3. For a slider that is mapped to 100 different values for the purpose of recording assessments, the size to enter is 100. If no rating instrument is used (e.g. when evaluation gathers post-edits or qualitative feedback only), enter 'N/A'. What to enter in the text box: list, or give the range of, the possible values of the rating instrument. The list or range should be of the size specified in Question 4.3.3. If there are too many to list, use a range. E.g. for two-way forced-choice preference judgments, the list entered might be A better, B better; if there's also a no-preference option, the list might be A better, B better, neither. For a slider that is mapped to 100 different values for the purpose of recording assessments, the range 1-100 might be entered. If no rating instrument is used (e.g. when evaluation gathers post-edits or qualitative feedback only), enter 'N/A'.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Question 4.3.5: How is the scale or other rating instrument presented to evaluators? If none match, select 'Other' and describe.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Multiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 Multiple-choice options: choose this option if evaluators select exactly one of multiple options.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 Check-boxes: choose this option if evaluators select any number of options from multiple given options.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 Slider: choose this option if evaluators move a pointer on a slider scale to the position corresponding to their assessment.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 N/A (there is no rating instrument): choose this option if there is no rating instrument.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 Other (please specify): choose this option if there is a rating instrument, but none of the above adequately describe the way you present it to evaluators. Use the text box to describe the rating instrument and link to a screenshot. What to enter in the text box: Copy and paste the verbatim text that evaluators see during each assessment, that is intended to convey the evaluation task to them. E.g. Which of these texts do you prefer?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Or Make any corrections to this text that you think are necessary in order to improve it to the point where you would be happy to provide it to a client. Multiple-choice options (select one): 9",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 (dis)agreement with quality statement: Participants specify the degree to which they agree with a given quality statement by indicating their agreement on a rating instrument. The rating instrument is labelled with degrees of agreement and can additionally have numerical labels. E.g. This text is fluent -1=strongly disagree...5=strongly agree.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 direct quality estimation: Participants are asked to provide a rating using a rating instrument, which typically (but not always) mentions the quality criterion explicitly. E.g. How fluent is this text? -1=not at all fluent...5=very fluent.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 relative quality estimation (including ranking):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Participants evaluate two or more items in terms of which is better. E.g. Rank these texts in terms of fluency; Which of these texts is more fluent?; Which of these items do you prefer?.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 counting occurrences in text: Evaluators are asked to count how many times some type of phenomenon occurs, e.g. the number of facts contained in the output that are inconsistent with the input.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "9 Explanations adapted from Howcroft et al. (2020) .",
	"cite_spans": [
	{
	"start": 28,
	"end": 50,
	"text": "Howcroft et al. (2020)",
	"ref_id": "BIBREF1"
	}
	],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 qualitative feedback (e.g. via comments entered in a text box): Typically, these are responses to open-ended questions in a survey or interview.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 evaluation through post-editing/annotation:",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Choose this option if the evaluators' task consists of editing or inserting annotations in text. E.g. evaluators may perform error correction and edits are then automatically measured to yield a numerical score.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 output classification or labelling: Choose this option if evaluators assign outputs to categories. E.g. What is the overall sentiment of this piece of text? -Positive/neutral/negative.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 user-text interaction measurements: choose this option if participants in the evaluation experiment interact with a text in some way, and measurements are taken of their interaction. E.g. reading speed, eye movement tracking, comprehension questions, etc. Excludes situations where participants are given a task to solve and their performance is measured which comes under the next option.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 task performance measurements: choose this option if participants in the evaluation experiment are given a task to perform, and measurements are taken of their performance at the task. E.g. task is finding information, and task performance measurement is task completion speed and success rate.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 user-system interaction measurements: choose this option if participants in the evaluation experiment interact with a system in some way, while measurements are taken of their interaction. E.g. duration of interaction, hyperlinks followed, number of likes, or completed sales.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "\u2022 Other (please specify): Use the text box to describe the form of response elicitation used in assessing the quality criterion if it doesn't fall in any of the above categories.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Question 4.3.9: How are raw responses from participants aggregated or otherwise processed to obtain reported scores for this quality criterion? State if no scores reported.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: normally a set of separate assessments is collected from evaluators and is converted to the results as reported. Describe here the method(s) used in the conversion(s). E.g. macro-averages or micro-averages are computed from numerical scores to provide summary, persystem results.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Question 4.3.10: Method(s) used for determining effect size and significance of findings for this quality criterion.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: A list of methods used for calculating the effect size and significance of any results, both as reported in the paper given in Question 1.1, for this quality criterion. If none calculated, state 'None'. What to enter in the text box: the methods used to compute, and results obtained from, any measures of inter-annotator and intra-annotator agreement obtained for the quality criterion.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "A.5 Ethics Questions (Questions 5.1-5.4)",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "The questions in this section relate to ethical aspects of the evaluation. Information can be entered in the text box provided, and/or by linking to a source where complete information can be found.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Question 5.1: Has the evaluation experiment this sheet is being completed for, or the larger study it is part of, been approved by a research ethics committee? If yes, which research ethics committee?",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: Typically, research organisations, universities and other highereducation institutions require some form ethical approval before experiments involving human participants, however innocuous, are permitted to proceed. Please provide here the name of the body that approved the experiment, or state 'No' if approval has not (yet) been obtained.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Question 5.2: Do any of the system outputs (or human-authored stand-ins) evaluated, or do any of the responses collected, in the experiment contain personal data (as defined in GDPR Art. 4, \u00a71: https://gdpr.eu/article-4-definitions/)? If yes, describe data and state how addressed.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: State 'No' if no personal data as defined by GDPR was recorded or collected, otherwise explain how conformity with GDPR requirements such as privacy and security was ensured, e.g. by linking to the (successful) application for ethics approval from Question 5.1.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Question 5.3: Do any of the system outputs (or human-authored stand-ins) evaluated, or do any of the responses collected, in the experiment contain special category information (as defined in GDPR Art. 9, \u00a71: https://gdpr.eu/article-9-processing-specialcategories-of-personal-data-prohibited/)? If yes, describe data and state how addressed.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: State 'No' if no special-category data as defined by GDPR was recorded or collected, otherwise explain how conformity with GDPR requirements relating to special-category data was ensured, e.g. by linking to the (successful) application for ethics approval from Question 5.1.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "Question 5.4: Have any impact assessments been carried out for the evaluation experiment, and/or any data collected/evaluated in connection with it? If yes, summarise approach(es) and outcomes.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "What to enter in the text box: Use this box to describe any ex ante or ex post impact assessments that have been carried out in relation to the evaluation experiment, such that the assessment plan and process, as well as the outcomes, were captured in written form. Link to documents if possible. Types of impact assessment include data protection impact assessments, e.g. under GDPR. 10 Environmental and social impact assessment frameworks are also available.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "A.4.3 Response elicitation (Questions 4.3.1-4.3.11)",
	"sec_num": null
	},
	{
	"text": "https://gem-benchmark.com/data_cards/ guide 2 https://aclrollingreview.org/ responsibleNLPresearch/",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "",
	"sec_num": null
	},
	{
	"text": "https://reprogen.github.io/2021/",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "",
	"sec_num": null
	},
	{
	"text": "We take all examples of quality criteria from published reports of evaluations, via the annotated database compiled byHowcroft et al. (2020).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "",
	"sec_num": null
	},
	{
	"text": "We use the term 'human generation' where the items being evaluated have been created manually, rather than generated by an automatic system.",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "",
	"sec_num": null
	},
	{
	"text": "https://en.wikipedia.org/wiki/List_ of_ISO_639-1_codesMultiple-choice options (select one):",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "",
	"sec_num": null
	},
	{
	"text": "We take all examples of quality criteria from published reports of evaluations, via the annotated database compiled byHowcroft et al. (2020).",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "",
	"sec_num": null
	},
	{
	"text": "https://ico.org.uk/for-organisations/ guide-to-data-protection/ guide-to-the-general-data-protection-regulation-gdpr/ accountability-and-governance/ data-protection-impact-assessments/",
	"cite_spans": [],
	"ref_spans": [],
	"eq_spans": [],
	"section": "",
	"sec_num": null
	}
	],
	"back_matter": [],
	"bib_entries": {
	"BIBREF0": {
	"ref_id": "b0",
	"title": "Abstract Meaning Representation for sembanking",
	"authors": [
	{
	"first": "Laura",
	"middle": [],
	"last": "Banarescu",
	"suffix": ""
	},
	{
	"first": "Claire",
	"middle": [],
	"last": "Bonial",
	"suffix": ""
	},
	{
	"first": "Shu",
	"middle": [],
	"last": "Cai",
	"suffix": ""
	},
	{
	"first": "Madalina",
	"middle": [],
	"last": "Georgescu",
	"suffix": ""
	},
	{
	"first": "Kira",
	"middle": [],
	"last": "Griffitt",
	"suffix": ""
	},
	{
	"first": "Ulf",
	"middle": [],
	"last": "Hermjakob",
	"suffix": ""
	},
	{
	"first": "Kevin",
	"middle": [],
	"last": "Knight",
	"suffix": ""
	},
	{
	"first": "Philipp",
	"middle": [],
	"last": "Koehn",
	"suffix": ""
	},
	{
	"first": "Martha",
	"middle": [],
	"last": "Palmer",
	"suffix": ""
	},
	{
	"first": "Nathan",
	"middle": [],
	"last": "Schneider",
	"suffix": ""
	}
	],
	"year": 2013,
	"venue": "Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse",
	"volume": "",
	"issue": "",
	"pages": "178--186",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "Laura Banarescu, Claire Bonial, Shu Cai, Madalina Georgescu, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Philipp Koehn, Martha Palmer, and Nathan Schneider. 2013. Abstract Meaning Representation for sembanking. In Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Dis- course, pages 178-186, Sofia, Bulgaria. Association for Computational Linguistics.",
	"links": null
	},
	"BIBREF1": {
	"ref_id": "b1",
	"title": "Disentangling the properties of human evaluation methods: A classification system to support comparability, meta-evaluation and reproducibility testing",
	"authors": [
	{
	"first": "Anya",
	"middle": [],
	"last": "Belz",
	"suffix": ""
	},
	{
	"first": "Simon",
	"middle": [],
	"last": "Mille",
	"suffix": ""
	},
	{
	"first": "David",
	"middle": [
	"M"
	],
	"last": "Howcroft",
	"suffix": ""
	}
	],
	"year": 2020,
	"venue": "Proceedings of the 13th International Conference on Natural Language Generation",
	"volume": "",
	"issue": "",
	"pages": "183--194",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "Anya Belz, Simon Mille, and David M. Howcroft. 2020. Disentangling the properties of human evaluation methods: A classification system to support compa- rability, meta-evaluation and reproducibility testing. In Proceedings of the 13th International Conference on Natural Language Generation, pages 183-194, Dublin, Ireland. Association for Computational Lin- guistics.",
	"links": null
	},
	"BIBREF2": {
	"ref_id": "b2",
	"title": "The ReproGen shared task on reproducibility of human evaluations in NLG: Overview and results",
	"authors": [
	{
	"first": "Anya",
	"middle": [],
	"last": "Belz",
	"suffix": ""
	},
	{
	"first": "Anastasia",
	"middle": [],
	"last": "Shimorina",
	"suffix": ""
	},
	{
	"first": "Shubham",
	"middle": [],
	"last": "Agarwal",
	"suffix": ""
	},
	{
	"first": "Ehud",
	"middle": [],
	"last": "Reiter",
	"suffix": ""
	}
	],
	"year": 2021,
	"venue": "The 14th International Conference on Natural Language Generation",
	"volume": "",
	"issue": "",
	"pages": "",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "Anya Belz, Anastasia Shimorina, Shubham Agarwal, and Ehud Reiter. 2021. The ReproGen shared task on reproducibility of human evaluations in NLG: Overview and results. In The 14th International Con- ference on Natural Language Generation.",
	"links": null
	},
	"BIBREF3": {
	"ref_id": "b3",
	"title": "Data statements for natural language processing: Toward mitigating system bias and enabling better science",
	"authors": [
	{
	"first": "Emily",
	"middle": [
	"M"
	],
	"last": "Bender",
	"suffix": ""
	},
	{
	"first": "Batya",
	"middle": [],
	"last": "Friedman",
	"suffix": ""
	}
	],
	"year": 2018,
	"venue": "Transactions of the Association for Computational Linguistics",
	"volume": "6",
	"issue": "",
	"pages": "587--604",
	"other_ids": {
	"DOI": [
	"10.1162/tacl_a_00041"
	]
	},
	"num": null,
	"urls": [],
	"raw_text": "Emily M. Bender and Batya Friedman. 2018. Data statements for natural language processing: Toward mitigating system bias and enabling better science. Transactions of the Association for Computational Linguistics, 6:587-604.",
	"links": null
	},
	"BIBREF4": {
	"ref_id": "b4",
	"title": "With little power comes great responsibility",
	"authors": [
	{
	"first": "Dallas",
	"middle": [],
	"last": "Card",
	"suffix": ""
	},
	{
	"first": "Peter",
	"middle": [],
	"last": "Henderson",
	"suffix": ""
	},
	{
	"first": "Urvashi",
	"middle": [],
	"last": "Khandelwal",
	"suffix": ""
	},
	{
	"first": "Robin",
	"middle": [],
	"last": "Jia",
	"suffix": ""
	},
	{
	"first": "Kyle",
	"middle": [],
	"last": "Mahowald",
	"suffix": ""
	},
	{
	"first": "Dan",
	"middle": [],
	"last": "Jurafsky",
	"suffix": ""
	}
	],
	"year": 2020,
	"venue": "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
	"volume": "",
	"issue": "",
	"pages": "9263--9274",
	"other_ids": {
	"DOI": [
	"10.18653/v1/2020.emnlp-main.745"
	]
	},
	"num": null,
	"urls": [],
	"raw_text": "Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, and Dan Jurafsky. 2020. With little power comes great responsibility. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 9263-9274, Online. Association for Computa- tional Linguistics.",
	"links": null
	},
	"BIBREF5": {
	"ref_id": "b5",
	"title": "Show your work: Improved reporting of experimental results",
	"authors": [
	{
	"first": "Jesse",
	"middle": [],
	"last": "Dodge",
	"suffix": ""
	},
	{
	"first": "Suchin",
	"middle": [],
	"last": "Gururangan",
	"suffix": ""
	},
	{
	"first": "Dallas",
	"middle": [],
	"last": "Card",
	"suffix": ""
	},
	{
	"first": "Roy",
	"middle": [],
	"last": "Schwartz",
	"suffix": ""
	},
	{
	"first": "Noah",
	"middle": [
	"A"
	],
	"last": "Smith",
	"suffix": ""
	}
	],
	"year": 2019,
	"venue": "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
	"volume": "",
	"issue": "",
	"pages": "2185--2194",
	"other_ids": {
	"DOI": [
	"10.18653/v1/D19-1224"
	]
	},
	"num": null,
	"urls": [],
	"raw_text": "Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, and Noah A. Smith. 2019. Show your work: Improved reporting of experimental results. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Lan- guage Processing (EMNLP-IJCNLP), pages 2185- 2194, Hong Kong, China. Association for Computa- tional Linguistics.",
	"links": null
	},
	"BIBREF7": {
	"ref_id": "b7",
	"title": "The GEM benchmark: Natural language generation, its evaluation and metrics",
	"authors": [
	{
	"first": "Sebastian",
	"middle": [],
	"last": "Gehrmann",
	"suffix": ""
	},
	{
	"first": "Tosin",
	"middle": [],
	"last": "Adewumi",
	"suffix": ""
	},
	{
	"first": "Karmanya",
	"middle": [],
	"last": "Aggarwal",
	"suffix": ""
	},
	{
	"first": "Pawan",
	"middle": [],
	"last": "Sasanka Ammanamanchi",
	"suffix": ""
	},
	{
	"first": "Anuoluwapo",
	"middle": [],
	"last": "Aremu",
	"suffix": ""
	},
	{
	"first": "Antoine",
	"middle": [],
	"last": "Bosselut",
	"suffix": ""
	},
	{
	"first": "Miruna-Adriana",
	"middle": [],
	"last": "Khyathi Raghavi Chandu",
	"suffix": ""
	},
	{
	"first": "Dipanjan",
	"middle": [],
	"last": "Clinciu",
	"suffix": ""
	},
	{
	"first": "Kaustubh",
	"middle": [],
	"last": "Das",
	"suffix": ""
	},
	{
	"first": "Wanyu",
	"middle": [],
	"last": "Dhole",
	"suffix": ""
	},
	{
	"first": "Esin",
	"middle": [],
	"last": "Du",
	"suffix": ""
	},
	{
	"first": "Ond\u0159ej",
	"middle": [],
	"last": "Durmus",
	"suffix": ""
	},
	{
	"first": "Chris",
	"middle": [
	"Chinenye"
	],
	"last": "Du\u0161ek",
	"suffix": ""
	},
	{
	"first": "Varun",
	"middle": [],
	"last": "Emezue",
	"suffix": ""
	},
	{
	"first": "Cristina",
	"middle": [],
	"last": "Gangal",
	"suffix": ""
	},
	{
	"first": "Tatsunori",
	"middle": [],
	"last": "Garbacea",
	"suffix": ""
	},
	{
	"first": "Yufang",
	"middle": [],
	"last": "Hashimoto",
	"suffix": ""
	},
	{
	"first": "Yacine",
	"middle": [],
	"last": "Hou",
	"suffix": ""
	},
	{
	"first": "Harsh",
	"middle": [],
	"last": "Jernite",
	"suffix": ""
	},
	{
	"first": "Yangfeng",
	"middle": [],
	"last": "Jhamtani",
	"suffix": ""
	},
	{
	"first": "Shailza",
	"middle": [],
	"last": "Ji",
	"suffix": ""
	},
	{
	"first": "Mihir",
	"middle": [],
	"last": "Jolly",
	"suffix": ""
	},
	{
	"first": "Dhruv",
	"middle": [],
	"last": "Kale",
	"suffix": ""
	},
	{
	"first": "Faisal",
	"middle": [],
	"last": "Kumar",
	"suffix": ""
	},
	{
	"first": "Aman",
	"middle": [],
	"last": "Ladhak",
	"suffix": ""
	},
	{
	"first": "Mounica",
	"middle": [],
	"last": "Madaan",
	"suffix": ""
	},
	{
	"first": "Khyati",
	"middle": [],
	"last": "Maddela",
	"suffix": ""
	},
	{
	"first": "Saad",
	"middle": [],
	"last": "Mahajan",
	"suffix": ""
	},
	{
	"first": "",
	"middle": [],
	"last": "Mahamood",
	"suffix": ""
	}
	],
	"year": 2021,
	"venue": "Proceedings of the 1st Workshop on Natural Language Generation",
	"volume": "",
	"issue": "",
	"pages": "96--120",
	"other_ids": {
	"DOI": [
	"10.18653/v1/2021.gem-1.10"
	]
	},
	"num": null,
	"urls": [],
	"raw_text": "Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Anuoluwapo Aremu, Antoine Bosselut, Khy- athi Raghavi Chandu, Miruna-Adriana Clinciu, Dipanjan Das, Kaustubh Dhole, Wanyu Du, Esin Durmus, Ond\u0159ej Du\u0161ek, Chris Chinenye Emezue, Varun Gangal, Cristina Garbacea, Tatsunori Hashimoto, Yufang Hou, Yacine Jernite, Harsh Jham- tani, Yangfeng Ji, Shailza Jolly, Mihir Kale, Dhruv Kumar, Faisal Ladhak, Aman Madaan, Mounica Maddela, Khyati Mahajan, Saad Mahamood, Bod- hisattwa Prasad Majumder, Pedro Henrique Martins, Angelina McMillan-Major, Simon Mille, Emiel van Miltenburg, Moin Nadeem, Shashi Narayan, Vitaly Nikolaev, Andre Niyongabo Rubungo, Salomey Osei, Ankur Parikh, Laura Perez-Beltrachini, Niranjan Ramesh Rao, Vikas Raunak, Juan Diego Rodriguez, Sashank Santhanam, Jo\u00e3o Sedoc, Thibault Sellam, Samira Shaikh, Anastasia Shimo- rina, Marco Antonio Sobrevilla Cabezudo, Hendrik Strobelt, Nishant Subramani, Wei Xu, Diyi Yang, Akhila Yerukola, and Jiawei Zhou. 2021. The GEM benchmark: Natural language generation, its evaluation and metrics. In Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021), pages 96-120, Online. Association for Computational Linguistics.",
	"links": null
	},
	"BIBREF8": {
	"ref_id": "b8",
	"title": "Emiel van Miltenburg, Sashank Santhanam, and Verena Rieser. 2020. Twenty years of confusion in human evaluation: NLG needs evaluation sheets and standardised definitions",
	"authors": [
	{
	"first": "David",
	"middle": [
	"M"
	],
	"last": "Howcroft",
	"suffix": ""
	},
	{
	"first": "Anya",
	"middle": [],
	"last": "Belz",
	"suffix": ""
	},
	{
	"first": "Miruna-Adriana",
	"middle": [],
	"last": "Clinciu",
	"suffix": ""
	},
	{
	"first": "Dimitra",
	"middle": [],
	"last": "Gkatzia",
	"suffix": ""
	},
	{
	"first": "A",
	"middle": [],
	"last": "Sadid",
	"suffix": ""
	},
	{
	"first": "Saad",
	"middle": [],
	"last": "Hasan",
	"suffix": ""
	},
	{
	"first": "Simon",
	"middle": [],
	"last": "Mahamood",
	"suffix": ""
	},
	{
	"first": "",
	"middle": [],
	"last": "Mille",
	"suffix": ""
	}
	],
	"year": null,
	"venue": "Proceedings of the 13th International Conference on Natural Language Generation",
	"volume": "",
	"issue": "",
	"pages": "169--182",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "David M. Howcroft, Anya Belz, Miruna-Adriana Clinciu, Dimitra Gkatzia, Sadid A. Hasan, Saad Mahamood, Simon Mille, Emiel van Miltenburg, Sashank Santhanam, and Verena Rieser. 2020. Twenty years of confusion in human evaluation: NLG needs evaluation sheets and standardised definitions. In Proceedings of the 13th International Conference on Natural Language Generation, pages 169-182, Dublin, Ireland. Association for Computational Lin- guistics.",
	"links": null
	},
	"BIBREF9": {
	"ref_id": "b9",
	"title": "What happens if you treat ordinal ratings as interval data? human evaluations in NLP are even more underpowered than you think",
	"authors": [
	{
	"first": "M",
	"middle": [],
	"last": "David",
	"suffix": ""
	},
	{
	"first": "Verena",
	"middle": [],
	"last": "Howcroft",
	"suffix": ""
	},
	{
	"first": "",
	"middle": [],
	"last": "Rieser",
	"suffix": ""
	}
	],
	"year": 2021,
	"venue": "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
	"volume": "",
	"issue": "",
	"pages": "8932--8939",
	"other_ids": {
	"DOI": [
	"10.18653/v1/2021.emnlp-main.703"
	]
	},
	"num": null,
	"urls": [],
	"raw_text": "David M. Howcroft and Verena Rieser. 2021. What happens if you treat ordinal ratings as interval data? human evaluations in NLP are even more under- powered than you think. In Proceedings of the 2021 Conference on Empirical Methods in Natural Lan- guage Processing, pages 8932-8939, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.",
	"links": null
	},
	"BIBREF10": {
	"ref_id": "b10",
	"title": "From discourse to logic: Introduction to modeltheoretic semantics of natural language, formal logic and discourse representation theory",
	"authors": [
	{
	"first": "Hans",
	"middle": [],
	"last": "Kamp",
	"suffix": ""
	},
	{
	"first": "Uwe",
	"middle": [],
	"last": "Reyle",
	"suffix": ""
	}
	],
	"year": 2013,
	"venue": "",
	"volume": "42",
	"issue": "",
	"pages": "",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "Hans Kamp and Uwe Reyle. 2013. From discourse to logic: Introduction to modeltheoretic semantics of natural language, formal logic and discourse rep- resentation theory, volume 42. Springer Science & Business Media.",
	"links": null
	},
	"BIBREF11": {
	"ref_id": "b11",
	"title": "Model cards for model reporting",
	"authors": [
	{
	"first": "Margaret",
	"middle": [],
	"last": "Mitchell",
	"suffix": ""
	},
	{
	"first": "Simone",
	"middle": [],
	"last": "Wu",
	"suffix": ""
	},
	{
	"first": "Andrew",
	"middle": [],
	"last": "Zaldivar",
	"suffix": ""
	},
	{
	"first": "Parker",
	"middle": [],
	"last": "Barnes",
	"suffix": ""
	},
	{
	"first": "Lucy",
	"middle": [],
	"last": "Vasserman",
	"suffix": ""
	},
	{
	"first": "Ben",
	"middle": [],
	"last": "Hutchinson",
	"suffix": ""
	},
	{
	"first": "Elena",
	"middle": [],
	"last": "Spitzer",
	"suffix": ""
	},
	{
	"first": "Deborah",
	"middle": [],
	"last": "Inioluwa",
	"suffix": ""
	},
	{
	"first": "Timnit",
	"middle": [],
	"last": "Raji",
	"suffix": ""
	},
	{
	"first": "",
	"middle": [],
	"last": "Gebru",
	"suffix": ""
	}
	],
	"year": 2019,
	"venue": "Proceedings of the Conference on Fairness, Accountability, and Transparency, FAT* '19",
	"volume": "",
	"issue": "",
	"pages": "220--229",
	"other_ids": {
	"DOI": [
	"10.1145/3287560.3287596"
	]
	},
	"num": null,
	"urls": [],
	"raw_text": "Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru. 2019. Model cards for model reporting. In Proceedings of the Conference on Fairness, Account- ability, and Transparency, FAT* '19, page 220-229, New York, NY, USA. Association for Computing Machinery.",
	"links": null
	},
	"BIBREF12": {
	"ref_id": "b12",
	"title": "Why we need new evaluation metrics for NLG",
	"authors": [
	{
	"first": "Jekaterina",
	"middle": [],
	"last": "Novikova",
	"suffix": ""
	},
	{
	"first": "Ond\u0159ej",
	"middle": [],
	"last": "Du\u0161ek",
	"suffix": ""
	},
	{
	"first": "Amanda",
	"middle": [
	"Cercas"
	],
	"last": "Curry",
	"suffix": ""
	},
	{
	"first": "Verena",
	"middle": [],
	"last": "Rieser",
	"suffix": ""
	}
	],
	"year": 2017,
	"venue": "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
	"volume": "",
	"issue": "",
	"pages": "2241--2252",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "Jekaterina Novikova, Ond\u0159ej Du\u0161ek, Amanda Cercas Curry, and Verena Rieser. 2017. Why we need new evaluation metrics for NLG. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2241-2252.",
	"links": null
	},
	"BIBREF13": {
	"ref_id": "b13",
	"title": "A structured review of the validity of BLEU",
	"authors": [
	{
	"first": "Ehud",
	"middle": [],
	"last": "Reiter",
	"suffix": ""
	}
	],
	"year": 2018,
	"venue": "Computational Linguistics",
	"volume": "44",
	"issue": "3",
	"pages": "393--401",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "Ehud Reiter. 2018. A structured review of the validity of BLEU. Computational Linguistics, 44(3):393-401.",
	"links": null
	},
	"BIBREF14": {
	"ref_id": "b14",
	"title": "An investigation into the validity of some metrics for automatically evaluating natural language generation systems",
	"authors": [
	{
	"first": "Ehud",
	"middle": [],
	"last": "Reiter",
	"suffix": ""
	},
	{
	"first": "Anya",
	"middle": [],
	"last": "Belz",
	"suffix": ""
	}
	],
	"year": 2009,
	"venue": "Computational Linguistics",
	"volume": "35",
	"issue": "4",
	"pages": "529--558",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "Ehud Reiter and Anya Belz. 2009. An investigation into the validity of some metrics for automatically evalu- ating natural language generation systems. Computa- tional Linguistics, 35(4):529-558.",
	"links": null
	},
	"BIBREF15": {
	"ref_id": "b15",
	"title": "The human evaluation datasheet 1.0: A template for recording details of human evaluation experiments in NLP",
	"authors": [
	{
	"first": "Anastasia",
	"middle": [],
	"last": "Shimorina",
	"suffix": ""
	},
	{
	"first": "Anya",
	"middle": [],
	"last": "Belz",
	"suffix": ""
	}
	],
	"year": 2021,
	"venue": "",
	"volume": "",
	"issue": "",
	"pages": "",
	"other_ids": {
	"arXiv": [
	"arXiv:2103.09710v1"
	]
	},
	"num": null,
	"urls": [],
	"raw_text": "Anastasia Shimorina and Anya Belz. 2021. The human evaluation datasheet 1.0: A template for recording de- tails of human evaluation experiments in NLP. ArXiv preprint arXiv:2103.09710v1.",
	"links": null
	},
	"BIBREF16": {
	"ref_id": "b16",
	"title": "Emiel van Miltenburg, and Emiel Krahmer. 2021. Human evaluation of automatically generated text: Current trends and best practice guidelines",
	"authors": [
	{
	"first": "Chris",
	"middle": [],
	"last": "Van Der Lee",
	"suffix": ""
	},
	{
	"first": "Albert",
	"middle": [],
	"last": "Gatt",
	"suffix": ""
	}
	],
	"year": null,
	"venue": "Computer Speech & Language",
	"volume": "67",
	"issue": "",
	"pages": "",
	"other_ids": {
	"DOI": [
	"10.1016/j.csl.2020.101151"
	]
	},
	"num": null,
	"urls": [],
	"raw_text": "Chris van der Lee, Albert Gatt, Emiel van Miltenburg, and Emiel Krahmer. 2021. Human evaluation of automatically generated text: Current trends and best practice guidelines. Computer Speech & Language, 67:101151.",
	"links": null
	},
	"BIBREF17": {
	"ref_id": "b17",
	"title": "Best practices for the human evaluation of automatically generated text",
	"authors": [
	{
	"first": "Chris",
	"middle": [],
	"last": "Van Der Lee",
	"suffix": ""
	},
	{
	"first": "Albert",
	"middle": [],
	"last": "Gatt",
	"suffix": ""
	},
	{
	"first": "Sander",
	"middle": [],
	"last": "Emiel Van Miltenburg",
	"suffix": ""
	},
	{
	"first": "Emiel",
	"middle": [],
	"last": "Wubben",
	"suffix": ""
	},
	{
	"first": "",
	"middle": [],
	"last": "Krahmer",
	"suffix": ""
	}
	],
	"year": 2019,
	"venue": "Proceedings of the 12th International Conference on Natural Language Generation",
	"volume": "",
	"issue": "",
	"pages": "355--368",
	"other_ids": {},
	"num": null,
	"urls": [],
	"raw_text": "Chris van der Lee, Albert Gatt, Emiel van Miltenburg, Sander Wubben, and Emiel Krahmer. 2019. Best practices for the human evaluation of automatically generated text. In Proceedings of the 12th Interna- tional Conference on Natural Language Generation, pages 355-368.",
	"links": null
	}
	},
	"ref_entries": {
	"FIGREF0": {
	"text": "Question 4.2.2: Are outputs assessed in absolute or relative terms?",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF2": {
	"text": "Question 4.3.4: List or range of possible values of the scale or other rating instrument. Enter 'N/A', if there is no rating instrument.",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF3": {
	"text": "Question 4.3.8: Form of response elicitation. If none match, select 'Other' and describe. Multiple-choice options (select one): 5 5 Explanations adapted from Howcroft et al. (2020).",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF4": {
	"text": "Question 4.3.11: Has the inter-annotator and intra-annotator agreement between evaluators for this quality criterion been measured? If yes, what method was used, and what are the agreement scores?",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF5": {
	"text": "deep linguistic representation (DLR): any of a variety of deep, underspecified, semantic representations, such as abstract meaning representations (AMRs; Banarescu et al., 2013) or discourse representation structures (DRSs; Kamp and Reyle, 2013).",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF6": {
	"text": "deep linguistic representation (DLR): any of a variety of deep, underspecified, semantic representations, such as abstract meaning representations (AMRs; Banarescu et al., 2013) or discourse representation structures (DRSs; Kamp and Reyle, 2013).",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF7": {
	"text": "Input Language(s), or 'N/A'.",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF8": {
	"text": "Question 4.2.1: Does an individual assessment involve an objective or a subjective judgment?",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF9": {
	"text": "Question 4.3.4: List or range of possible values of the scale or other rating instrument. Enter 'N/A', if there is no rating instrument.",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF10": {
	"text": "",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF11": {
	"text": "Question 4.3.8: Form of response elicitation. If none match, select 'Other' and describe.",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"FIGREF12": {
	"text": "Question 4.3.11: Has the inter-annotator and intra-annotator agreement between evaluators for this quality criterion been measured? If yes, what method was used, and what are the agreement scores?",
	"type_str": "figure",
	"uris": null,
	"num": null
	},
	"TABREF1": {
	"html": null,
	"num": null,
	"type_str": "table",
	"text": "Question 4.3.3: Size of scale or other rating instrument (i.e. how many different possible values there are). Answer should be an integer or 'continuous' (if it's not possible to state how many possible responses there are). Enter 'N/A' if there is no rating instrument.",
	"content": "<table/>"
	},
	"TABREF5": {
	"html": null,
	"num": null,
	"type_str": "table",
	"text": "Question 3.3.2: How are responses collected? E.g. paper forms, online survey tool, etc.",
	"content": "<table><tr><td>What to enter in the text box: Use this space to</td><td/></tr><tr><td>describe how you collected responses, e.g. paper</td><td/></tr><tr><td>forms, Google forms, SurveyMonkey, Mechanical</td><td/></tr><tr><td>Turk, CrowdFlower, audio/video recording, etc.</td><td/></tr><tr><td>Question 3.3.3: What quality assurance methods are used? Select all that apply. If none match, select 'Other' and describe. In all cases, provide details in the text box un-der 'Other'.</td><td/></tr><tr><td>Check-box options (select all that apply):</td><td/></tr><tr><td>automatic quality checking methods are used during/post evaluation: evaluations are checked for quality by automatic scripts during</td><td/></tr><tr><td>or after evaluations, e.g. evaluators are given</td><td/></tr><tr><td>known bad/good outputs to check they're given</td><td/></tr><tr><td>bad/good scores on MTurk.</td><td/></tr><tr><td>manual quality checking methods are used evaluations are during/post evaluation: checked for quality by a manual process during or after evaluations, e.g. scores assigned by eval-uators are monitored by researchers conducting</td><td>This might include geographic location of IP address, educational level, or demographic informa-tion such as gender, age, etc. Where characteristics differ among evaluators (e.g. gender, age, location etc.), also give numbers for each subgroup.</td></tr><tr><td>the experiment.</td><td>3.3.1-3.3.8 A.3.3 Experimental Design Questions</td></tr><tr><td/><td>Questions 3.3.1-3.3.8 record information about the</td></tr><tr><td/><td>experimental design of the evaluation experiment.</td></tr><tr><td/><td>Question 3.3.1: Has the experimental design been preregistered? If yes, on which reg-istry?</td></tr></table>"
	},
	"TABREF6": {
	"html": null,
	"num": null,
	"type_str": "table",
	"text": "Question 4.3.1: What do you call the quality criterion in explanations/interfaces to evaluators? Enter 'N/A' if criterion not named.",
	"content": "<table><tr><td>cover-ing what is presented to evaluators, how they se-lect response and via what type of tool, etc. The eleven questions (4.3.1-4.3.11) are based on the information annotated in the large scale survey of human evaluation methods in NLG by Howcroft et al. (2020). What to enter in the text box: the name you use to refer to the quality criterion in explanations and/or interfaces created for evaluators. Examples of qual-ity criterion names include Fluency, Clarity, Mean-ing Preservation. If no name is used, state 'N/A'. Question 4.3.2: What definition do you give for the quality criterion in explana-tions/interfaces to evaluators? Enter 'N/A' if no definition given. What to enter in the text box: Copy and past the ver-batim definition you give to evaluators to explain the quality criterion they're assessing. If you don't explicitly call it a definition, enter the nearest thing to a definition you give them. If you don't give any definition, state 'N/A'. Question 4.3.3: Size of scale or other rating instrument (i.e. how many different possi-ble values there are). Answer should be an integer or 'continuous' (if it's not possible to state how many possible responses there are). Enter 'N/A' if there is no rating instru-ment.</td></tr></table>"
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