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{"yuvalkirstain--contract_nli_t5_lm": {"description": "\nSCROLLS: Standardized CompaRison Over Long Language Sequences.\nA suite of natural language datasets that require reasoning over long texts.\nhttps://scrolls-benchmark.com/\n\nContract NLI (Koreeda and Manning, 2021) is a natural language inference dataset in the legal domain.\nGiven a non-disclosure agreement (the premise), the task is to predict whether a particular legal statement (the hypothesis) is entailed, not entailed (neutral), or cannot be entailed (contradiction) from the contract.\nThe NDAs were manually picked after simple filtering from the Electronic Data Gathering, Analysis, and Retrieval system (EDGAR) and Google.\nThe dataset contains a total of 607 contracts and 17 unique hypotheses, which were combined to produce the dataset's 10,319 examples.", "citation": "@inproceedings{koreeda-manning-2021-contractnli,\n title = \"ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts\",\n author = \"Koreeda, Yuta and\n Manning, Christopher D.\",\n booktitle = \"Findings of the Association for Computational Linguistics: EMNLP 2021\",\n year = \"2021\",\n publisher = \"Association for Computational Linguistics\"\n}\n\n\n@article{ TODO citation here\n}\nNote that each SCROLLS dataset has its own citation. Please see the source to\nget the correct citation for each contained dataset.\n", "homepage": "https://stanfordnlp.github.io/contract-nli/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "pid": {"dtype": "string", "id": null, "_type": "Value"}, "input": {"dtype": "string", "id": null, "_type": "Value"}, "output": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": null, "config_name": null, "version": null, "splits": {"train": {"name": "train", "num_bytes":
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{"yuvalkirstain--contract_nli_t5_lm": {"description": "\nSCROLLS: Standardized CompaRison Over Long Language Sequences.\nA suite of natural language datasets that require reasoning over long texts.\nhttps://scrolls-benchmark.com/\n\nContract NLI (Koreeda and Manning, 2021) is a natural language inference dataset in the legal domain.\nGiven a non-disclosure agreement (the premise), the task is to predict whether a particular legal statement (the hypothesis) is entailed, not entailed (neutral), or cannot be entailed (contradiction) from the contract.\nThe NDAs were manually picked after simple filtering from the Electronic Data Gathering, Analysis, and Retrieval system (EDGAR) and Google.\nThe dataset contains a total of 607 contracts and 17 unique hypotheses, which were combined to produce the dataset's 10,319 examples.", "citation": "@inproceedings{koreeda-manning-2021-contractnli,\n title = \"ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts\",\n author = \"Koreeda, Yuta and\n Manning, Christopher D.\",\n booktitle = \"Findings of the Association for Computational Linguistics: EMNLP 2021\",\n year = \"2021\",\n publisher = \"Association for Computational Linguistics\"\n}\n\n\n@article{ TODO citation here\n}\nNote that each SCROLLS dataset has its own citation. Please see the source to\nget the correct citation for each contained dataset.\n", "homepage": "https://stanfordnlp.github.io/contract-nli/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "pid": {"dtype": "string", "id": null, "_type": "Value"}, "input": {"dtype": "string", "id": null, "_type": "Value"}, "output": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": null, "config_name": null, "version": null, "splits": {"train": {"name": "train", "num_bytes": 16840375, "num_examples": 7191, "dataset_name": "contract_nli_t5_lm"}, "validation": {"name": "validation", "num_bytes": 2447438, "num_examples": 1037, "dataset_name": "contract_nli_t5_lm"}, "test": {"name": "test", "num_bytes": 2447438, "num_examples": 1037, "dataset_name": "contract_nli_t5_lm"}}, "download_checksums": null, "download_size": 2544858, "post_processing_size": null, "dataset_size": 21735251, "size_in_bytes": 24280109}}
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