Create legal_lama.py

legal_lama.py

@@ -0,0 +1,134 @@
+# 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.
+"""LegalLAMA: Legal LAnguage Model Analysis (LAMA) (LAMA) dataset."""
+
+import json
+import os
+import datasets
+
+
+MAIN_CITATION = """
+@inproceedings{chalkidis-garneau-etal-2023-lexlms,
+    title = {{LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development}},
+    author = "Chalkidis*, Ilias and 
+              Garneau*, Nicolas and
+              Goanta, Catalina and 
+              Katz, Daniel Martin and 
+              Søgaard, Anders",
+    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics",
+    month = july,
+    year = "2023",
+    address = "Toronto, Canada",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/xxx",
+}
+"""
+
+_DESCRIPTION = """LegalLAMA: Legal LAnguage Model Analysis (LAMA) (LAMA) dataset."""
+MAIN_PATH = 'https://huggingface.co/datasets/lexlms/legal_lama/resolve/main'
+
+
+class LegalLAMAConfig(datasets.BuilderConfig):
+    """BuilderConfig for XAI - Fairness."""
+
+    def __init__(
+        self,
+        data_url,
+        **kwargs,
+    ):
+        """BuilderConfig for LegalLAMA.
+
+        Args:
+          data_url: `string`, url to download the zip file from
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(LegalLAMAConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        self.data_url = data_url
+
+
+class LegalLAMA(datasets.GeneratorBasedBuilder):
+    """LegalLAMA: A multilingual benchmark for evaluating fairness in legal text processing. Version 1.0"""
+
+    BUILDER_CONFIGS = [
+        LegalLAMAConfig(
+            name="canadian_crimes",
+            data_url=os.path.join(MAIN_PATH, "canadian_crimes.jsonl"),
+        ),
+        LegalLAMAConfig(
+            name="canadian_sections",
+            data_url=os.path.join(MAIN_PATH, "canadian_sections.jsonl"),
+        ),
+        LegalLAMAConfig(
+            name="cjeu_terms",
+            data_url=os.path.join(MAIN_PATH, "cjeu_terms.jsonl"),
+        ),
+        LegalLAMAConfig(
+            name="ecthr_terms",
+            data_url=os.path.join(MAIN_PATH, "ecthr_terms.jsonl"),
+        ),
+        LegalLAMAConfig(
+            name="ecthr_articles",
+            data_url=os.path.join(MAIN_PATH, "ecthr_articles.jsonl"),
+        ),
+        LegalLAMAConfig(
+            name="us_crimes",
+            data_url=os.path.join(MAIN_PATH, "us_crimes.jsonl"),
+        ),
+        LegalLAMAConfig(
+            name="us_terms",
+            data_url=os.path.join(MAIN_PATH, "us_terms.jsonl"),
+        ),
+        LegalLAMAConfig(
+            name="contract_types",
+            data_url=os.path.join(MAIN_PATH, "contract_types.jsonl"),
+        ),
+        LegalLAMAConfig(
+            name="contract_sections",
+            data_url=os.path.join(MAIN_PATH, "contract_sections.jsonl"),
+        ),
+    ]
+
+    def _info(self):
+        features = {"text": datasets.Value("string"), "label": datasets.Value("string")}
+        return datasets.DatasetInfo(
+            description=self.config.description,
+            features=datasets.Features(features),
+            homepage="https://huggingface.co/datasets/lexlms/legal_lama",
+            citation=MAIN_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download(self.config.data_url)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": data_dir,
+                    "split": "test",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """This function returns the examples in the raw (text) form."""
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+                example = {
+                    "text": data["masked_sentences"][0],
+                    "label": data["obj_label"],
+                }
+                yield id_, example