SituatedQA / SituatedQA.py
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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
"""SituatedQA: Incorporating Extra-Linguistic Contexts into QA."""
import json
import re
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@article{ zhang2021situatedqa,
title={ {S}ituated{QA}: Incorporating Extra-Linguistic Contexts into {QA} },
author={ Zhang, Michael J.Q. and Choi, Eunsol },
journal={ Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) },
year={ 2021 }
}
"""
_DESCRIPTION = """\
"""
_URL = "https://raw.githubusercontent.com/mikejqzhang/SituatedQA/master/data/qa_data/"
_URLS = {
"geo_train": _URL + "geo.train.jsonl",
"geo_dev": _URL + "geo.dev.jsonl",
"geo_test": _URL + "geo.test.jsonl",
"temp_train": _URL + "temp.train.jsonl",
"temp_dev": _URL + "temp.dev.jsonl",
"temp_test": _URL + "temp.test.jsonl",
}
class SituatedQAConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
"""BuilderConfig
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(SituatedQAConfig, self).__init__(**kwargs)
class Squall(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
SituatedQAConfig(name = 'geo'),
SituatedQAConfig(name = 'temp')]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"question": datasets.Value("string"),
"id": datasets.Value("string"),
"edited_question": datasets.Value("string"),
"date": datasets.Value("string"),
"date_type": datasets.Value("string"),
"location": datasets.Value("string"),
"answer": datasets.features.Sequence(datasets.Value("string")),
"any_answer": datasets.features.Sequence(datasets.Value("string")),
}
),
# No default supervised_keys (as we have to pass both question
# and context as input).
supervised_keys=None,
homepage="https://github.com/mikejqzhang/SituatedQA/tree/master",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
urls_to_download = {
"geo_train": _URLS["geo_train"],
"geo_dev": _URLS["geo_dev"],
"geo_test": _URLS["geo_test"],
"temp_train": _URLS["temp_train"],
"temp_dev": _URLS["temp_dev"],
"temp_test": _URLS["temp_test"],
}
downloaded_files = dl_manager.download_and_extract(urls_to_download)
if self.config.name == 'geo':
train_file = downloaded_files["geo_train"]
dev_file = downloaded_files["geo_dev"]
test_file = downloaded_files["geo_test"]
else:
train_file = downloaded_files["temp_train"]
dev_file = downloaded_files["temp_dev"]
test_file = downloaded_files["temp_test"]
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"split_key": "train", "filepath": train_file}),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"split_key": "dev", "filepath": dev_file}),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"split_key": "test", "filepath": test_file}),
]
def _generate_examples(self, split_key, filepath):
"""This function returns the examples in the raw (text) form."""
logger.info("generating examples from = %s", filepath)
with open(filepath, 'r') as file:
json_list = list(file)
for i, line in enumerate(json_list):
data = json.loads(line)
if 'location' not in data:
data['location']=''
if 'date' not in data:
data['date']=''
if 'date_type' not in data:
data['date_type']=''
yield i, {
"question": data["question"],
"id": str(data["id"]),
"edited_question": data["edited_question"],
"date": data["date"],
"date_type": data["date_type"],
"location": data["location"],
"answer": data["answer"],
"any_answer": data["any_answer"]
}