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import datasets |
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import json |
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from typing import List |
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import pandas as pd |
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import csv |
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_LICENSE = "http://www.apache.org/licenses/LICENSE-2.0" |
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_HOMEPAGE='https://huggingface.co/datasets/THUIR/T2Ranking' |
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_DESCRIPTION = 'T2Ranking: A large-scale Chinese benchmark for passage retrieval.' |
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_CITATION = """ |
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@misc{xie2023t2ranking, |
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title={T2Ranking: A large-scale Chinese Benchmark for Passage Ranking}, |
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author={Xiaohui Xie and Qian Dong and Bingning Wang and Feiyang Lv and Ting Yao and Weinan Gan and Zhijing Wu and Xiangsheng Li and Haitao Li and Yiqun Liu and Jin Ma}, |
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year={2023}, |
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eprint={2304.03679}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.IR} |
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} |
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""" |
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_URLS_DICT = { |
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"collection": "data/collection.tsv", |
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"qrels.train": "data/qrels.train.tsv", |
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"qrels.dev": "data/qrels.dev.tsv", |
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"qrels.retrieval.train": "data/qrels.retrieval.train.tsv", |
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"qrels.retrieval.dev": "data/qrels.retrieval.dev.tsv", |
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"queries.train": "data/queries.train.tsv", |
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"queries.test": "data/queries.test.tsv", |
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"queries.dev": "data/queries.dev.tsv", |
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"train.bm25.tsv": "data/train.bm25.tsv", |
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"train.mined.tsv": "data/train.mined.tsv", |
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} |
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_FEATURES_DICT = { |
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'collection': { |
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"pid": datasets.Value("int64"), |
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"text": datasets.Value("string"), |
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}, |
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'qrels.train': { |
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"qid": datasets.Value("int64"), |
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"-": datasets.Value("int64"), |
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"pid": datasets.Value("int64"), |
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"rel": datasets.Value("int64"), |
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}, |
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'qrels.retrieval.train': { |
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"qid": datasets.Value("int64"), |
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"pid": datasets.Value("int64"), |
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}, |
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'qrels.dev': { |
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"qid": datasets.Value("int64"), |
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"-": datasets.Value("int64"), |
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"pid": datasets.Value("int64"), |
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"rel": datasets.Value("int64"), |
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}, |
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'qrels.retrieval.dev': { |
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"qid": datasets.Value("int64"), |
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"pid": datasets.Value("int64"), |
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}, |
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'queries.train': { |
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"qid": datasets.Value("int64"), |
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"text": datasets.Value("string"), |
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}, |
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'queries.dev': { |
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"qid": datasets.Value("int64"), |
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"text": datasets.Value("string"), |
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}, |
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'queries.test': { |
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"qid": datasets.Value("int64"), |
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"text": datasets.Value("string"), |
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}, |
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"train.bm25.tsv": { |
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"qid": datasets.Value("int64"), |
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"pid": datasets.Value("int64"), |
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"index": datasets.Value("int64"), |
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}, |
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"train.mined.tsv": { |
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"qid": datasets.Value("int64"), |
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"pid": datasets.Value("int64"), |
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"index": datasets.Value("int64"), |
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"score": datasets.Value("float32"), |
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}, |
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} |
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class T2RankingConfig(datasets.BuilderConfig): |
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"""BuilderConfig for T2Ranking.""" |
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def __init__(self, splits, **kwargs): |
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super().__init__(version=datasets.Version("1.0.0"), **kwargs) |
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self.splits = splits |
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class T2Ranking(datasets.GeneratorBasedBuilder): |
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"""The T2Ranking benchmark.""" |
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BUILDER_CONFIGS = [ |
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T2RankingConfig( |
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name="collection", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="qrels.train", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="qrels.dev", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="queries.train", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="queries.dev", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="queries.test", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="qrels.retrieval.train", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="qrels.retrieval.dev", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="train.bm25.tsv", |
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splits=['train'], |
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), |
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T2RankingConfig( |
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name="train.mined.tsv", |
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splits=['train'], |
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), |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features(_FEATURES_DICT[self.config.name]), |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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license=_LICENSE, |
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) |
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
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split_things = [] |
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for split_name in self.config.splits: |
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split_data_path = _URLS_DICT[self.config.name] |
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filepath = dl_manager.download(split_data_path) |
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split_thing = datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": filepath, |
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} |
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) |
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split_things.append(split_thing) |
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return split_things |
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def _generate_examples(self, filepath): |
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reader = csv.DictReader(open(filepath), delimiter='\t', quoting=csv.QUOTE_NONE) |
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keys = _FEATURES_DICT[self.config.name].keys() |
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idx = -1 |
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for data in reader: |
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idx+=1 |
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yield idx, {key: data[key] for key in keys} |
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