Datasets:
Tasks:
Summarization
Languages:
English
Multilinguality:
monolingual
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
Tags:
License:
| 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, | |
| } | |