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README.md

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----
-license: cc-by-nc-sa-4.0
----

contract-nli.py

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-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""ContractNLI: A Benchmark Dataset for ContractNLI in English."""
-
-import json
-import os
-import textwrap
-
-import datasets
-
-MAIN_PATH = 'https://huggingface.co/datasets/cognitivplus/contract-nli/resolve/main'
-
-MAIN_CITATION = """\
- @inproceedings{koreeda-manning-2021-contractnli-dataset,
-    title = "{C}ontract{NLI}: A Dataset for Document-level Natural Language Inference for Contracts",
-    author = "Koreeda, Yuta  and
-      Manning, Christopher",
-    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
-    month = nov,
-    year = "2021",
-    address = "Punta Cana, Dominican Republic",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2021.findings-emnlp.164",
-    doi = "10.18653/v1/2021.findings-emnlp.164",
-    pages = "1907--1919",
-}"""
-
-_DESCRIPTION = """\
-ContractNLI: A Benchmark Dataset for ContractNLI in English
-"""
-
-
-CONTRACTNLI_LABELS = ["contradiction", "entailment", "neutral"]
-
-
-class ContractNLIConfig(datasets.BuilderConfig):
-    """BuilderConfig for ContractNLI."""
-
-    def __init__(
-        self,
-        url,
-        data_url,
-        data_file,
-        citation,
-        label_classes=None,
-        **kwargs,
-    ):
-        """BuilderConfig for ContractNLI.
-
-        Args:
-          url: `string`, url for the original project
-          data_url: `string`, url to download the zip file from
-          data_file: `string`, filename for data set
-          citation: `string`, citation for the data set
-          url: `string`, url for information about the data set
-          label_classes: `list[string]`, the list of classes if the label is
-            categorical. If not provided, then the label will be of type
-            `datasets.Value('float32')`.
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(ContractNLIConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-        self.label_classes = label_classes
-        self.url = url
-        self.data_url = data_url
-        self.data_file = data_file
-        self.citation = citation
-
-
-class ContractNLI(datasets.GeneratorBasedBuilder):
-    """ContractNLI: A Benchmark Dataset for ContractNLI in English. Version 1.0"""
-
-    BUILDER_CONFIGS = [
-        ContractNLIConfig(
-            name="contractnli_a",
-            description=textwrap.dedent(
-                """\
-            The ContractNLI dataset consists of Non-Disclosure Agreements (NDAs). All NDAs have been labeled based 
-            on several hypothesis templates as entailment, neutral or contradiction. In this version of the task
-            (Task A), the input consists of the relevant part of the document w.r.t. to the hypothesis.
-            """
-            ),
-            label_classes=CONTRACTNLI_LABELS,
-            data_url=f"{MAIN_PATH}/contract_nli.zip",
-            data_file="contract_nli_v1.jsonl",
-            url="https://stanfordnlp.github.io/ contract- nli/",
-            citation=textwrap.dedent(
-                """\
-            @inproceedings{koreeda-manning-2021-contractnli-dataset,
-                    title = "{C}ontract{NLI}: A Dataset for Document-level Natural Language Inference for Contracts",
-                    author = "Koreeda, Yuta  and
-                      Manning, Christopher",
-                    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
-                    month = nov,
-                    year = "2021",
-                    address = "Punta Cana, Dominican Republic",
-                    publisher = "Association for Computational Linguistics",
-                    url = "https://aclanthology.org/2021.findings-emnlp.164",
-                    doi = "10.18653/v1/2021.findings-emnlp.164",
-                    pages = "1907--1919",
-                }
-            }"""
-            ),
-        ),
-        ContractNLIConfig(
-            name="contractnli_b",
-            description=textwrap.dedent(
-                """\
-            The ContractNLI dataset consists of Non-Disclosure Agreements (NDAs). All NDAs have been labeled based 
-            on several hypothesis templates as entailment, neutral or contradiction. In this version of the task
-            (Task B), the input consists of the full document.
-            """
-            ),
-            label_classes=CONTRACTNLI_LABELS,
-            data_url=f"{MAIN_PATH}/contract_nli_long.zip",
-            data_file="contract_nli_long.jsonl",
-            url="https://stanfordnlp.github.io/ contract- nli/",
-            citation=textwrap.dedent(
-                """\
-            @inproceedings{koreeda-manning-2021-contractnli-dataset,
-                    title = "{C}ontract{NLI}: A Dataset for Document-level Natural Language Inference for Contracts",
-                    author = "Koreeda, Yuta  and
-                      Manning, Christopher",
-                    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
-                    month = nov,
-                    year = "2021",
-                    address = "Punta Cana, Dominican Republic",
-                    publisher = "Association for Computational Linguistics",
-                    url = "https://aclanthology.org/2021.findings-emnlp.164",
-                    doi = "10.18653/v1/2021.findings-emnlp.164",
-                    pages = "1907--1919",
-                }
-            }"""
-            ),
-        ),
-    ]
-
-    def _info(self):
-        features = {
-            "premise": datasets.Value("string"),
-            "hypothesis": datasets.Value("string"),
-            "label": datasets.ClassLabel(names=CONTRACTNLI_LABELS)
-        }
-
-        return datasets.DatasetInfo(
-            description=self.config.description,
-            features=datasets.Features(features),
-            homepage=self.config.url,
-            citation=self.config.citation + "\n" + MAIN_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(self.config.data_url)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, self.config.data_file), "split": "train"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, self.config.data_file), "split": "test"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, self.config.data_file),
-                    "split": "dev",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """This function returns the examples in the raw (text) form."""
-        if self.config.name == "contractnli_a":
-            with open(filepath, "r", encoding="utf-8") as f:
-                for id_, row in enumerate(f):
-                    data = json.loads(row)
-                    if data["subset"] == split:
-                        yield id_, {
-                            "premise": data["premise"],
-                            "hypothesis": data["hypothesis"],
-                            "label": data["label"],
-                        }
-        elif self.config.name == "contractnli_b":
-            with open(filepath, "r", encoding="utf-8") as f:
-                sid = -1
-                for id_, row in enumerate(f):
-                    data = json.loads(row)
-                    if data["subset"] == split:
-                        for sample in data['hypothesises/labels']:
-                            sid += 1
-                            yield sid, {
-                                "premise": data["premise"],
-                                "hypothesis": sample['hypothesis'],
-                                "label": sample['label'],
-                            }

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contract_nli_long.zip → contractnli_a/contract-nli-train.parquet

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contractnli_a/contract-nli-validation.parquet

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contractnli_b/contract-nli-test.parquet

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