import gzip import pandas as pd import datasets from datasets import DatasetInfo, GeneratorBasedBuilder, SplitGenerator, Split import csv from itertools import islice class FeverDataset(GeneratorBasedBuilder): VERSION = "1.0.0" _URLS = [ "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000000.tsv.gz", "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000001.tsv.gz", "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000002.tsv.gz", "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000003.tsv.gz", "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000004.tsv.gz", ] def _info(self): return DatasetInfo( description="FEVER Dataset with span annotations.", features=datasets.Features({ "query": datasets.Value("string"), "document": datasets.Value("string"), "spans": datasets.Value("string"), }), supervised_keys=None, homepage="https://huggingface.co/datasets/jinaai/fever-span-annotated", license="CC BY 4.0", splits={ "test": {"num_bytes": 0}, # Placeholder, will be updated later }, dataset_size=0, download_size=0 ) def _split_generators(self, dl_manager): urls_to_download = self._URLS downloaded_files = dl_manager.download_and_extract(urls_to_download) return [ SplitGenerator( name=Split.TEST, gen_kwargs={"file_paths": downloaded_files['test']}, ), ] def _generate_examples(self, file_paths): for file_path in file_paths: with gzip.open(file_path, 'rt') as file: reader = csv.reader( file, dialect='excel-tab' if self._dialect == 'tsv' else 'excel', ) for row in islice(reader, self._current_index, None, self._stride): if len(row) >= 3: yield row[0], { "query": row[0], "document": row[1], "spans": row[2], }