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# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
#
# 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
"""HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering."""
import json
import textwrap
import datasets
_CITATION = """
@inproceedings{xanh2020_2wikimultihop,
title = "Constructing A Multi-hop {QA} Dataset for Comprehensive Evaluation of Reasoning Steps",
author = "Ho, Xanh and
Duong Nguyen, Anh-Khoa and
Sugawara, Saku and
Aizawa, Akiko",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.coling-main.580",
pages = "6609--6625",
}
"""
_DESCRIPTION = """\
"""
_URL_BASE = "data"
class TwowikimultihopQA(datasets.GeneratorBasedBuilder):
"""2wikimultihopQA is a Dataset for Diverse, Explainable Multi-hop Question Answering."""
BUILDER_CONFIGS = [
datasets.BuilderConfig(),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"type": datasets.Value("string"),
"supporting_facts": datasets.features.Sequence(
{
"title": datasets.Value("string"),
"sent_id": datasets.Value("int32"),
}
),
"context": datasets.features.Sequence(
{
"title": datasets.Value("string"),
"sentences": datasets.features.Sequence(datasets.Value("string")),
}
),
"evidences": datasets.features.Sequence(
datasets.features.Sequence(
datasets.Value("string")
)
),
"entity_ids": datasets.Value("string")
}
),
supervised_keys=None,
homepage="https://github.com/Alab-NII/2wikimultihop",
citation=_CITATION,
)
def _split_generators(self, dl_manager: datasets.DownloadManager):
"""Returns SplitGenerators."""
paths = {
datasets.Split.TRAIN: f"{_URL_BASE}/train.json",
datasets.Split.VALIDATION: f"{_URL_BASE}/dev.json",
datasets.Split.TEST: f"{_URL_BASE}/test.json",
}
files = dl_manager.download(paths)
split_generators = []
for split in files:
split_generators.append(datasets.SplitGenerator(name=split, gen_kwargs={"data_file": files[split]}))
return split_generators
def _generate_examples(self, data_file):
"""This function returns the examples."""
data = json.load(open(data_file))
for idx, example in enumerate(data):
# Test set has missing keys
for k in ["answer", "type", "level"]:
if k not in example.keys():
example[k] = None
if "supporting_facts" not in example.keys():
example["supporting_facts"] = []
yield idx, {
"id": example["_id"],
"question": example["question"],
"answer": example["answer"],
"type": example["type"],
"supporting_facts": [{"title": f[0], "sent_id": f[1]} for f in example["supporting_facts"]],
"context": [{"title": f[0], "sentences": f[1]} for f in example["context"]],
"evidences": example["evidences"],
"entity_ids": example["entity_ids"]
}
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