import json import os from typing import Any, Dict, List, Tuple, Union import datasets from datasets.tasks import Summarization logger = datasets.logging.get_logger(__name__) def _load_jsonl(filename): with open(filename, "r") as fp: jsonl_content = fp.read() result = [json.loads(jline) for jline in jsonl_content.splitlines()] return result def _load_json(filepath): with open(filepath, "r") as fp: res = json.load(fp) return res _CITATION = """ @article{Shen2022MultiLexSum, author = {Zejiang Shen and Kyle Lo and Lauren Yu and Nathan Dahlberg and Margo Schlanger and Doug Downey}, title = {Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularities}, journal = {CoRR}, volume = {abs/2206.10883}, year = {2022}, url = {https://doi.org/10.48550/arXiv.2206.10883}, doi = {10.48550/arXiv.2206.10883} } """ # TODO _DESCRIPTION = """ Multi-LexSum is a multi-doc summarization dataset for civil rights litigation lawsuits with summaries of three granularities. """ # TODO: Update with full abstract _HOMEPAGE = "https://multilexsum.github.io" # _BASE_URL = "https://ai2-s2-research.s3.us-west-2.amazonaws.com/multilexsum/releases" _BASE_URL = "https://huggingface.co/datasets/allenai/multi_lexsum/resolve/main/releases" _FILES = { "train": "train.json", "dev": "dev.json", "test": "test.json", "sources": "sources.json", } class MultiLexsumConfig(datasets.BuilderConfig): """BuilderConfig for LexSum.""" def __init__(self, **kwargs): """BuilderConfig for LexSum. Args: **kwargs: keyword arguments forwarded to super. """ super(MultiLexsumConfig, self).__init__(**kwargs) class MultiLexsum(datasets.GeneratorBasedBuilder): """MultiLexSum Dataset: a multi-doc summarization dataset for civil rights litigation lawsuits with summaries of three granularities. """ BUILDER_CONFIGS = [ MultiLexsumConfig( name="v20220616", version=datasets.Version("1.0.0", "Public v1.0 release."), description="The v1.0 Multi-LexSum dataset", ), MultiLexsumConfig( name="v20230518", version=datasets.Version("1.1.0", "Public v1.1 release."), description="It adds additional metadata for documents and cases", ), ] def _info(self): if self.config.name == "v20220616": return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "id": datasets.Value("string"), "sources": datasets.Sequence(datasets.Value("string")), "summary/long": datasets.Value("string"), "summary/short": datasets.Value("string"), "summary/tiny": datasets.Value("string"), } ), supervised_keys=None, homepage=_HOMEPAGE, citation=_CITATION, task_templates=[ Summarization(text_column="source", summary_column="summary/long") ], ) elif self.config.name == "v20230518": return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "id": datasets.Value("string"), "sources": datasets.Sequence(datasets.Value("string")), "sources_metadata": datasets.Sequence( { "doc_id": datasets.Value("string"), "doc_type": datasets.Value("string"), "doc_title": datasets.Value("string"), "parser": datasets.Value("string"), "is_ocr": datasets.Value("bool"), "url": datasets.Value("string"), } ), "summary/long": datasets.Value("string"), "summary/short": datasets.Value("string"), "summary/tiny": datasets.Value("string"), "case_metadata": datasets.Features( { # fmt: off "case_name": datasets.Value("string"), "case_type": datasets.Value("string"), "filing_date": datasets.Value("string"), "filing_year": datasets.Value("string"), "case_ongoing": datasets.Value("string"), "case_ongoing_record_time": datasets.Value("string"), "closing_year": datasets.Value("string"), "order_start_year": datasets.Value("string"), "order_end_year": datasets.Value("string"), "defendant_payment": datasets.Value("string"), "class_action_sought": datasets.Value("string"), "class_action_granted": datasets.Value("string"), "attorney_orgs": [datasets.Value("string")], "prevailing_party": datasets.Value("string"), "plaintiff_types": [datasets.Value("string")], "plaintiff_description": datasets.Value("string"), "constitutional_clauses": [datasets.Value("string")], "causes_of_action": [datasets.Value("string")], "summary_authors": [datasets.Value("string")], "case_url": datasets.Value("string"), # fmt: on } ), } ), supervised_keys=None, homepage=_HOMEPAGE, citation=_CITATION, task_templates=[ Summarization(text_column="source", summary_column="summary/long") ], ) def _split_generators(self, dl_manager): base_url = _BASE_URL if self.config.data_dir is None else self.config.data_dir downloaded_files = dl_manager.download_and_extract( { name: f"{base_url}/{self.config.name}/{filename}" for name, filename in _FILES.items() } ) # Given sources is a large file, we read it first sources = _load_json(downloaded_files["sources"]) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "subset_file": downloaded_files["train"], "sources": sources, }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "subset_file": downloaded_files["dev"], "sources": sources, }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "subset_file": downloaded_files["test"], "sources": sources, }, ), ] def _generate_examples(self, subset_file: str, sources: Dict[str, Dict]): """This function returns the examples in the raw (text) form.""" logger.info(f"generating examples from = {subset_file}") if self.config.name == "v20220616": subset_cases = _load_jsonl(subset_file) for case_data in subset_cases: case_sources = [ sources[source_id]["doc_text"] for source_id in case_data["case_documents"] ] yield case_data["case_id"], { "id": case_data["case_id"], "sources": case_sources, "summary/long": case_data["summary/long"], "summary/short": case_data["summary/short"], "summary/tiny": case_data["summary/tiny"], } elif self.config.name == "v20230518": subset_cases = _load_jsonl(subset_file) for idx, case_data in enumerate(subset_cases): case_sources = [ sources[source_id]["doc_text"] for source_id in case_data["case_documents"] ] case_source_metadata = [ { key: val for key, val in sources[source_id].items() if key != "doc_text" } for source_id in case_data["case_documents"] ] case_metadata = { "case_name": case_data["case_name"], "case_type": case_data["case_type"], "filing_date": case_data["filing_date"], "filing_year": case_data["filing_year"], "case_ongoing": case_data["case_ongoing"], "case_ongoing_record_time": case_data["case_ongoing_record_time"], "closing_year": case_data["closing_year"], "order_start_year": case_data["order_start_year"], "order_end_year": case_data["order_end_year"], "defendant_payment": case_data["defendant_payment"], "class_action_sought": case_data["class_action_sought"], "class_action_granted": case_data["class_action_granted"], "attorney_orgs": case_data["attorney_org"], "prevailing_party": case_data["prevailing_party"], "plaintiff_types": case_data["plaintiff_types"], "plaintiff_description": case_data["plaintiff_description"], "constitutional_clauses": case_data["constitutional_clauses"], "causes_of_action": case_data["causes_of_action"], "summary_authors": case_data["summary_authors"], "case_url": case_data["case_url"], } yield case_data["case_id"], { "id": case_data["case_id"], "sources": case_sources, "sources_metadata": case_source_metadata, "summary/long": case_data["summary/long"], "summary/short": case_data["summary/short"], "summary/tiny": case_data["summary/tiny"], "case_metadata": case_metadata, }