Update README.md

README.md

@@ -1,94 +1,173 @@
 ---
-license: apache-2.0
+license: cc-by-4.0
 task_categories:
-- translation
+  - translation
 language:
-- kk
-- ru
-- en
+  - kk
+  - ru
+  - en
 tags:
-- code
-pretty_name: Multilingual Literature Parallel Corpus
+  - machine-translation
+  - parallel-corpus
+  - multilingual
+  - literature
+  - kazakh
+  - russian
+  - english
+  - low-resource-language
+pretty_name: KazLit-Parallel
 size_categories:
-- 10K<n<100K
+  - 10K<n<100K
 ---
 
-# Dataset Card for Multilingual Literature Parallel Corpus
+# KazLit-Parallel
 
-<!-- Provide a quick summary of the dataset. -->
+**KazLit-Parallel** is a multilingual literary parallel corpus containing aligned text pairs in **Kazakh, Russian, and English**. The corpus is designed primarily for machine translation and multilingual NLP research involving Kazakh.
 
-The Multilingual Literature Parallel Corpus is designed for translation tasks, containing parallel text pairs from literature in three languages: Kazakh (kaz_Cyrl), Russian (rus_Cyrl), and English (eng_Latn).
+The current release contains **71,096 parallel text pairs** across six translation directions.
 
 ## Dataset Details
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
+KazLit-Parallel provides automatically aligned text segments derived from literary works available in Kazakh, Russian, and English.
 
-The Multilingual Literature Parallel Corpus provides parallel text pairs for translation tasks across Kazakh, Russian, and English. The dataset is curated to support the development of machine translation models by offering high-quality parallel sentences from literature.
+The corpus was created to expand the availability of parallel data involving Kazakh, which remains comparatively underrepresented in multilingual NLP resources. In addition to Kazakh–Russian and Kazakh–English pairs, the dataset includes Russian–English parallel data derived from the same broader literary collection.
 
-- **Language(s) (NLP):** Kazakh, Russian, English
-- **License:** Apache-2.0
+Potential applications include:
 
-## Uses
+- machine translation involving Kazakh;
+- multilingual representation learning;
+- cross-lingual NLP;
+- sentence-alignment research;
+- computational literary studies;
+- comparative analysis of translations across Kazakh, Russian, and English.
 
-<!-- Address questions around how the dataset is intended to be used. -->
+The corpus was constructed through automatic alignment and has not undergone exhaustive manual validation.
 
-### Direct Use
+- **Dataset name:** KazLit-Parallel
+- **Full name:** KazLit-Parallel: A Kazakh–Russian–English Literary Parallel Corpus
+- **Languages:** Kazakh, Russian, English
+- **Scripts:** Cyrillic for Kazakh and Russian; Latin for English
+- **Primary task:** Machine translation
+- **Number of parallel pairs:** 71,096
+- **License:** CC BY 4.0, subject to the licensing note below
 
-<!-- This section describes suitable use cases for the dataset. -->
+## Dataset Structure
 
-The dataset is suitable for developing and benchmarking translation models, cross-linguistic analysis, and linguistic research in the context of Kazakh, Russian, and English literature.
+Each example contains a source text segment and its corresponding target-language segment.
 
-### Out-of-Scope Use
+### Data Fields
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+- **`Language_pair`**: Translation direction in the format `source_to_target`, for example `kaz_to_eng`.
+- **`X`**: Source-language text.
+- **`y`**: Target-language text.
+- **`X_lang`**: Language of the source text.
+- **`y_lang`**: Language of the target text.
+- **`Similarity`**: Similarity score associated with the aligned source–target pair.
 
-The dataset is not suitable for non-literary text translation tasks, real-time translation applications, or any use cases requiring domain-specific jargon outside literature.
+### Language Pairs
 
-## Dataset Structure
+| Translation direction | Number of examples |
+| --------------------- | -----------------: |
+| `rus_to_eng`          |             23,856 |
+| `rus_to_kaz`          |             19,832 |
+| `eng_to_rus`          |             15,690 |
+| `eng_to_kaz`          |              5,534 |
+| `kaz_to_eng`          |              3,884 |
+| `kaz_to_rus`          |              2,300 |
+| **Total**             |         **71,096** |
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+The number of examples varies across translation directions, and this imbalance should be considered when constructing training and evaluation subsets.
 
-- **Language_pair**: The language pair in the format source_to_target (e.g., kaz_to_eng).
-- **X**: The source text.
-- **y**: The translated text.
-- **X_lang**: The language of the source text.
-- **y_lang**: The language of the translated text.
-- **Similarity**: The similarity score between the source and target texts.
+## Dataset Creation
 
-### Language Pairs and Example Counts
+### Motivation
 
-- **rus_to_eng**: 23,856 examples
-- **rus_to_kaz**: 19,832 examples
-- **eng_to_rus**: 15,690 examples
-- **eng_to_kaz**: 5,534 examples
-- **kaz_to_eng**: 3,884 examples
-- **kaz_to_rus**: 2,300 examples
+Parallel corpora involving Kazakh are substantially less abundant than comparable resources for higher-resource languages such as English and Russian.
 
-## Dataset Creation
+KazLit-Parallel was created to provide a larger literary parallel resource involving Kazakh and to support research in machine translation, multilingual NLP, and cross-lingual text analysis.
 
-### Curation Rationale
+Literary translations provide naturally occurring multilingual correspondences between texts while also exhibiting linguistic phenomena such as paraphrasing, restructuring, and non-literal translation. This makes the corpus relevant both for machine translation and for research on multilingual literary text.
 
-<!-- Motivation for the creation of this dataset. -->
+### Source Data
 
-The dataset was created to enhance the quality and accessibility of machine translation models for Kazakh, Russian, and English, specifically within the literary domain.
+The source material consists of literary works and their available translations in Kazakh, Russian, and English.
 
-### Source Data
+Where multiple language versions of the same work were available, the texts were processed and aligned to identify corresponding multilingual segments.
+
+### Data Collection and Processing
+
+The general construction pipeline consisted of:
+
+1. collecting corresponding literary texts in Kazakh, Russian, and/or English;
+2. extracting textual content;
+3. preprocessing and normalizing the texts;
+4. identifying corresponding multilingual works;
+5. automatically aligning source and target segments;
+6. computing similarity scores for candidate alignments; and
+7. organizing the resulting pairs by translation direction.
+
+The alignment process was performed automatically.
+
+## Uses
+
+### Intended Uses
+
+KazLit-Parallel is intended as a research resource for:
+
+- training and fine-tuning machine translation systems;
+- multilingual language-model training and adaptation;
+- Kazakh–Russian and Kazakh–English translation research;
+- cross-lingual representation learning;
+- sentence-alignment experiments;
+- multilingual and comparative literary analysis;
+- NLP research involving low-resource languages.
+
+For evaluation settings requiring manually verified reference translations, researchers may wish to construct a validated subset of the corpus.
+
+### Out-of-Scope Uses
+
+KazLit-Parallel is derived from literary texts and is therefore not intended to represent all domains or styles of contemporary language use.
+
+Results obtained using this corpus should not automatically be assumed to generalize to domains such as legal, medical, technical, conversational, or news translation without additional evaluation.
+
+## Dataset Quality and Limitations
+
+KazLit-Parallel was constructed using automatic text processing and alignment procedures. As a result, some alignment noise may be present.
+
+Literary translation is also frequently non-literal. Translators may restructure sentences, paraphrase passages, combine or divide segments, or adapt expressions for the target language. Consequently, lexical similarity alone should not be interpreted as a definitive measure of translation quality.
+
+The six translation directions are also unevenly represented, and the corpus is specific to the literary domain. These characteristics should be considered when designing experiments and interpreting results.
+
+## Licensing
+
+KazLit-Parallel is released under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license for components of the dataset for which the dataset creator holds the applicable rights.
+
+Under CC BY 4.0, these materials may be shared and adapted, including for commercial purposes, provided appropriate attribution is given.
 
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+### Underlying Literary Works
 
-The source data consists of original literary texts in Kazakh, Russian, and English.
+The copyright status of the underlying literary works and translations is separate from the rights associated with the compilation, processing, alignment, and metadata of KazLit-Parallel.
 
-### Target Data
+Individual source works or translations may remain subject to copyright held by their respective authors, translators, publishers, or other rights holders. Users are responsible for ensuring that their use of the underlying material complies with applicable copyright law and licensing conditions.
 
-The source data consists of translated literary texts in Kazakh, Russian, and English.
+## Ethical Considerations
 
-#### Data Collection and Processing
+The dataset consists of previously published literary material rather than text collected directly from human participants.
 
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
+Literary works may contain historically situated language, cultural assumptions, stereotypes, or other sensitive content originating from the source material. Models trained on the corpus may reproduce linguistic or cultural biases present in those texts.
 
-The data was collected from publicly available literary sources, preprocessed to align translations accurately, and normalized to maintain consistency in formatting and structure.
+## Citation
 
+If you use KazLit-Parallel in academic work, please cite the dataset:
 
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if
+```bibtex
+@misc{kazlitparallel,
+  title        = {KazLit-Parallel: A Kazakh--Russian--English Literary Parallel Corpus},
+  author       = {Abdashim, Sagi},
+  howpublished = {Hugging Face Datasets},
+  year         = {2024},
+  note         = {Dataset}
+}
+```