Datasets:

miracl
/

miracl

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# Licensed under the Apache License, Version 2.0 (the 'License');
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an 'AS IS' BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.

	# Lint as: python3

	import json
	import datasets
	from collections import defaultdict
	from dataclasses import dataclass

	_CITATION = '''
	'''

	surprise_languages = ['de', 'yo']
	new_languages = ['es', 'fa', 'fr', 'hi', 'zh'] + surprise_languages
	languages = ['ar', 'bn', 'en', 'es', 'fa', 'fi', 'fr', 'hi', 'id', 'ja', 'ko', 'ru', 'sw', 'te', 'th', 'zh'] + surprise_languages

	_DESCRIPTION = 'dataset load script for MIRACL'

	_DATASET_URLS = {
	lang: {
	'dev': [
	f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/topics/topics.miracl-v1.0-{lang}-dev.tsv',
	f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/qrels/qrels.miracl-v1.0-{lang}-dev.tsv',
	],
	'testB': [
	f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/topics/topics.miracl-v1.0-{lang}-test-b.tsv',
	],
	} for lang in languages
	}
	for lang in languages:
	if lang in surprise_languages:
	continue
	_DATASET_URLS[lang]['train'] = [
	f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/topics/topics.miracl-v1.0-{lang}-train.tsv',
	f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/qrels/qrels.miracl-v1.0-{lang}-train.tsv',
	]


	for lang in languages:
	if lang in new_languages:
	continue
	_DATASET_URLS[lang]['testA'] = [
	f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/topics/topics.miracl-v1.0-{lang}-test-a.tsv',
	]

	def load_topic(fn):
	qid2topic = {}
	with open(fn, encoding="utf-8") as f:
	for line in f:
	qid, topic = line.strip().split('\t')
	qid2topic[qid] = topic
	return qid2topic


	def load_qrels(fn):
	if fn is None:
	return None

	qrels = defaultdict(dict)
	with open(fn, encoding="utf-8") as f:
	for line in f:
	qid, _, docid, rel = line.strip().split('\t')
	qrels[qid][docid] = int(rel)
	return qrels


	class MIRACL(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIGS = [datasets.BuilderConfig(
	version=datasets.Version('1.0.0'),
	name=lang, description=f'MIRACL dataset in language {lang}.'
	) for lang in languages
	]

	def _info(self):
	features = datasets.Features({
	'query_id': datasets.Value('string'),
	'query': datasets.Value('string'),

	'positive_passages': [{
	'docid': datasets.Value('string'),
	'text': datasets.Value('string'), 'title': datasets.Value('string')
	}],
	'negative_passages': [{
	'docid': datasets.Value('string'),
	'text': datasets.Value('string'), 'title': datasets.Value('string'),
	}],
	})

	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=features, # Here we define them above because they are different between the two configurations
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage='https://project-miracl.github.io',
	# License for the dataset if available
	license='',
	# Citation for the dataset
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	lang = self.config.name
	downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[lang])

	splits = [
	datasets.SplitGenerator(
	name='dev',
	gen_kwargs={
	'filepaths': downloaded_files['dev'],
	},
	),
	datasets.SplitGenerator(
	name='testB',
	gen_kwargs={
	'filepaths': downloaded_files['testB'],
	},
	),

	]
	if lang not in surprise_languages:
	splits.append(datasets.SplitGenerator(
	name='train',
	gen_kwargs={
	'filepaths': downloaded_files['train'],
	},
	))

	if lang not in new_languages:
	splits.append(datasets.SplitGenerator(
	name='testA',
	gen_kwargs={
	'filepaths': downloaded_files['testA'],
	},
	))
	return splits

	def _generate_examples(self, filepaths):
	lang = self.config.name
	miracl_corpus = datasets.load_dataset('miracl/miracl-corpus', lang)['train']
	docid2doc = {doc['docid']: (doc['title'], doc['text']) for doc in miracl_corpus}

	topic_fn, qrel_fn = (filepaths) if len(filepaths) == 2 else (filepaths[0], None)
	qid2topic = load_topic(topic_fn)
	qrels = load_qrels(qrel_fn)
	for qid in qid2topic:
	data = {}
	data['query_id'] = qid
	data['query'] = qid2topic[qid]

	pos_docids = [docid for docid, rel in qrels[qid].items() if rel == 1] if qrels is not None else []
	neg_docids = [docid for docid, rel in qrels[qid].items() if rel == 0] if qrels is not None else []
	data['positive_passages'] = [{
	'docid': docid,
	**dict(zip(['title', 'text'], docid2doc[docid]))
	} for docid in pos_docids if docid in docid2doc]
	data['negative_passages'] = [{
	'docid': docid,
	**dict(zip(['title', 'text'], docid2doc[docid]))
	} for docid in neg_docids if docid in docid2doc]
	yield qid, data