Update metadata/croissant.json
Browse files- metadata/croissant.json +189 -0
metadata/croissant.json
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{
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"@context": {
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"@language": "en",
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"@vocab": "https://schema.org/",
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"citeAs": "cr:citeAs",
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"column": "cr:column",
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"conformsTo": "dct:conformsTo",
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"cr": "http://mlcommons.org/croissant/",
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"rai": "http://mlcommons.org/croissant/RAI/",
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"data": {
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"@id": "cr:data",
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"@type": "@json"
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},
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"dataType": {
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"@id": "cr:dataType",
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"@type": "@vocab"
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},
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"dct": "http://purl.org/dc/terms/",
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"examples": {
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"@id": "cr:examples",
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"@type": "@json"
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},
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"extract": "cr:extract",
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"field": "cr:field",
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"fileProperty": "cr:fileProperty",
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"fileObject": "cr:fileObject",
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"fileSet": "cr:fileSet",
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"format": "cr:format",
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"includes": "cr:includes",
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"isLiveDataset": "cr:isLiveDataset",
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"jsonPath": "cr:jsonPath",
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"key": "cr:key",
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"md5": "cr:md5",
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"parentField": "cr:parentField",
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"path": "cr:path",
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"recordSet": "cr:recordSet",
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"references": "cr:references",
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"regex": "cr:regex",
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"repeated": "cr:repeated",
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"replace": "cr:replace",
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"sc": "https://schema.org/",
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"separator": "cr:separator",
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"source": "cr:source",
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"subField": "cr:subField",
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"transform": "cr:transform"
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},
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"@type": "sc:Dataset",
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"name": "seqBench",
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"description": "\nSeqBench is a tunable benchmark designed to probe and analyze sequential reasoning \ncapabilities in language models. This compact version contains instances with varied \ncomplexity. Each instance provides:\n- 'context': NLP problem.\n- 'completion': Solution.\n- 'complexity_parameters': A dictionary with L, B, N.\n- 'instance_metadata': Maze dimensions and agent/target names.\n- 'structural_details': Rich structural information (as a JSON string) including room mappings, \n adjacency lists, door/key details, and canonical facts for the underlying base maze.\n",
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"conformsTo": "http://mlcommons.org/croissant/1.0",
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"citeAs": "@misc{anonymous2025seqbench,\n author = {Anonymous Submission},\n title = {SeqBench: A Tunable Benchmark to Quantify Sequential Reasoning Limits of LLMs},\n year = {2025},\n publisher = {Proceedings of the Conference on Empirical Methods in Natural Language Processing},\n note = {Special Theme: Interdisciplinary Recontextualization of NLP},\n comment = {Dataset accessible at https://huggingface.co/datasets/emnlp-submission/seqBench}\n}",
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"license": "https://creativecommons.org/licenses/by/4.0/",
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"url": "https://huggingface.co/datasets/emnlp-submission/seqBench",
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"distribution": [
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{
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"@type": "cr:FileObject",
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"@id": "seqbench-jsonl-gz-file",
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"name": "seqbench-jsonl-gz-file",
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"description": "The main benchmark data file in gzipped JSONL format.",
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"contentUrl": "https://huggingface.co/datasets/emnlp-submission/seqBench/resolve/main/seqBench_compact.jsonl.gz",
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"encodingFormat": "application/gzip",
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"sha256": "2b58a2f7b65def3445f2572726d5ff30d5ecab9cc841fffcb57a8bceb937b0c3"
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}
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],
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"recordSet": [
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{
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"@type": "cr:RecordSet",
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"@id": "seqbench-records",
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"name": "seqbench-records",
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"description": "Individual instances from the SeqBench benchmark (extracted from gzipped JSONL).",
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"field": [
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{
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"@type": "cr:Field",
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"@id": "context",
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"name": "context",
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"dataType": "sc:Text",
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"source": {
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"fileObject": {
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"@id": "seqbench-jsonl-gz-file"
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},
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"extract": {
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"column": "context"
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}
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}
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},
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{
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"@type": "cr:Field",
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"@id": "completion",
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"name": "completion",
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"dataType": "sc:Text",
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"source": {
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"fileObject": {
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"@id": "seqbench-jsonl-gz-file"
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},
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"extract": {
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"column": "completion"
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}
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}
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},
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{
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"@type": "cr:Field",
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"@id": "logical_depth_L",
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"name": "logical_depth_L",
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"dataType": "sc:Integer",
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"source": {
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"fileObject": {
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"@id": "seqbench-jsonl-gz-file"
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},
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"extract": {
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"jsonPath": "complexity_parameters.logical_depth_L"
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}
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}
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},
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{
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"@type": "cr:Field",
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"@id": "backtracking_count_B",
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"name": "backtracking_count_B",
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"dataType": "sc:Integer",
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"source": {
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"fileObject": {
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"@id": "seqbench-jsonl-gz-file"
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},
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"extract": {
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"jsonPath": "complexity_parameters.backtracking_count_B"
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}
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}
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},
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{
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"@type": "cr:Field",
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"@id": "noise_ratio_N",
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"name": "noise_ratio_N",
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"dataType": "sc:Float",
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"source": {
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"fileObject": {
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"@id": "seqbench-jsonl-gz-file"
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},
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"extract": {
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"jsonPath": "complexity_parameters.noise_ratio_N"
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}
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}
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},
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{
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"@type": "cr:Field",
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"@id": "instance_id",
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"name": "instance_id",
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"dataType": "sc:Text",
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"source": {
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"fileObject": {
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"@id": "seqbench-jsonl-gz-file"
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},
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"extract": {
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"column": "instance_id"
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}
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}
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},
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{
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"@type": "cr:Field",
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"@id": "full_instance_metadata",
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"name": "full_instance_metadata",
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"description": "Full instance metadata as a JSON string (contains maze_rows, maze_cols, agent_name, target_name).",
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"dataType": "sc:Text",
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"source": {
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"fileObject": {
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"@id": "seqbench-jsonl-gz-file"
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},
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"extract": {
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"column": "instance_metadata"
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}
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}
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},
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{
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"@type": "cr:Field",
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"@id": "structural_details_json",
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"name": "structural_details_json",
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"description": "Full structural details as a JSON string.",
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"dataType": "sc:Text",
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"source": {
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"fileObject": {
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"@id": "seqbench-jsonl-gz-file"
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},
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"extract": {
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"column": "structural_details"
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}
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}
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}
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]
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}
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]
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}
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