Create new file

contract-nli.py

@@ -0,0 +1,218 @@
+# 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:
+          text_column: ``string`, name of the column in the jsonl file corresponding
+            to the text
+          label_column: `string`, name of the column in the jsonl file corresponding
+            to the label
+          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')`.
+          multi_label: `boolean`, True if the task is multi-label
+          dev_column: `string`, name for the development subset
+          **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.
+            """
+            ),
+            text_column="premise",
+            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.
+            """
+            ),
+            text_column="premise",
+            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'],
+                            }