"""PRES retrieval dataset""" import json import csv import os import datasets _DESCRIPTION = 'Reference: https://mklab.iti.gr/results/spanish-passage-retrieval-dataset/' _HOMEPAGE_URL = 'https://mklab.iti.gr/results/spanish-passage-retrieval-dataset/' _LANGUAGES = {'es': 'ES'} _VERSION = '1.0.0' URL = 'https://huggingface.co/datasets/jinaai/spanish_passage_retrieval/resolve/main/' class PRESConfig(datasets.BuilderConfig): """BuilderConfig for PRESConfig.""" def __init__(self, **kwargs): super(PRESConfig, self).__init__( version=datasets.Version(_VERSION, ''), **kwargs ), class PRES(datasets.GeneratorBasedBuilder): """The Spanish Passage Retrieval dataset (PRES)""" BUILDER_CONFIGS = [ datasets.BuilderConfig( name=name, description=f'{name.title()} of the Spanish Passage Retrieval dataset.', ) for name in ['corpus.sentences', 'corpus.documents', 'queries', 'qrels.s2s', 'qrels.s2p'] ] BUILDER_CONFIG_CLASS = PRESConfig def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._data = None def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "_id": datasets.Value("string"), "text": datasets.Value("string"), } ), supervised_keys=None, homepage=_HOMEPAGE_URL, ) def _split_generators(self, dl_manager): return [ datasets.SplitGenerator(name=datasets.Split.TEST), ] def _generate_examples( self, split: str = None, ): if not self._data: with open(os.path.join(URL, 'docs.json')) as f: docs = json.load(f) with open(os.path.join(URL, 'topics.json')) as f: topics = json.load(f) with open(os.path.join(URL, 'relevance_passages.json')) as f: rel_passages = json.load(f) corpus_sentences = [] corpus_documents = [] queries = dict() qrels_s2s = dict() qrels_s2p = dict() topic_to_queries = dict() for topic in topics['topics']: topic_to_queries[topic['number']] = [] for query in topic['queries']: qid = query['number'] queries[qid] = query['text'] topic_to_queries[topic['number']].append(qid) qrels_s2s[qid] = [] qrels_s2p[qid] = [] known_passage_ids = set() for annotated_topic in rel_passages['topics']: topic = annotated_topic['number'] for annotation in annotated_topic['annotations']: passage_id = f'doc_{annotation["docNo"]}_{annotation["start"]}_{annotation["end"]}' doc_id = f'doc_{annotation["docNo"]}' if passage_id not in known_passage_ids: corpus_sentences.append({'_id': passage_id, 'text': annotation['text']}) known_passage_ids.add(passage_id) for qid in topic_to_queries[topic]: qrels_s2s[qid].append(passage_id) qrels_s2p[qid].append(doc_id) for doc in docs['documents']: doc_id = f'doc_{doc["docNo"]}' corpus_documents.append({'_id': doc_id, 'text': doc['text']}) self._data = { 'corpus.sentences': corpus_sentences, 'corpus.documents': corpus_documents, 'queries': queries, 'qrels.s2s': qrels_s2s, 'qrels.s2p': qrels_s2p } if self.config.name not in self._data: raise ValueError(f'Unknown config name: {self.config.name}') if self.config.name.startswith('corpus'): for line in self._data[self.config.name]: yield line['_id'], line elif self.config.name == 'queries': for qid, query in self._data['queries'].items(): yield qid, { "_id": qid, "text": query, } elif self.config.name.startswith('qrels'): for qid, dids in self._data[self.config.name].items(): yield qid, { "_id": qid, "text": ' '.join(dids), }