Datasets:
Tasks:
Question Answering
Languages:
Thai
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
extended|other-iapp-wiki-qa-dataset
License:
import json | |
import os | |
import datasets | |
_CITATION = """\ | |
@dataset{kobkrit_viriyayudhakorn_2021_4539916, | |
author = {Kobkrit Viriyayudhakorn and | |
Charin Polpanumas}, | |
title = {iapp_wiki_qa_squad}, | |
month = feb, | |
year = 2021, | |
publisher = {Zenodo}, | |
version = 1, | |
doi = {10.5281/zenodo.4539916}, | |
url = {https://doi.org/10.5281/zenodo.4539916} | |
} | |
""" | |
_DESCRIPTION = """\ | |
`iapp_wiki_qa_squad` is an extractive question answering dataset from Thai Wikipedia articles. | |
It is adapted from [the original iapp-wiki-qa-dataset](https://github.com/iapp-technology/iapp-wiki-qa-dataset) | |
to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, resulting in | |
5761/742/739 questions from 1529/191/192 articles. | |
""" | |
class IappWikiQaSquadConfig(datasets.BuilderConfig): | |
def __init__(self, **kwargs): | |
"""BuilderConfig | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(IappWikiQaSquadConfig, self).__init__(**kwargs) | |
class IappWikiQaSquad(datasets.GeneratorBasedBuilder): | |
_DOWNLOAD_URL = "https://github.com/iapp-technology/iapp-wiki-qa-dataset/raw/main/squad_format/data.zip" | |
_TRAIN_FILE = "train.jsonl" | |
_VALID_FILE = "valid.jsonl" | |
_TEST_FILE = "test.jsonl" | |
BUILDER_CONFIGS = [ | |
IappWikiQaSquadConfig( | |
name="iapp_wiki_qa_squad", | |
version=datasets.Version("1.0.0"), | |
description=_DESCRIPTION, | |
), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# datasets.features.FeatureConnectors | |
features=datasets.Features( | |
{ | |
"question_id": datasets.Value("string"), | |
"article_id": datasets.Value("string"), | |
"title": datasets.Value("string"), | |
"context": datasets.Value("string"), | |
"question": datasets.Value("string"), | |
"answers": datasets.features.Sequence( | |
{ | |
"text": datasets.Value("string"), | |
"answer_start": datasets.Value("int32"), | |
"answer_end": datasets.Value("int32"), | |
} | |
), | |
} | |
), | |
# If there's a common (input, target) tuple from the features, | |
# specify them here. They'll be used if as_supervised=True in | |
# builder.as_dataset. | |
supervised_keys=None, | |
# Homepage of the dataset for documentation | |
homepage="https://github.com/iapp-technology/iapp-wiki-qa-dataset/", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
arch_path = dl_manager.download_and_extract(self._DOWNLOAD_URL) | |
data_dir = os.path.join(arch_path, "data") | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={"filepath": os.path.join(data_dir, self._TRAIN_FILE)}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={"filepath": os.path.join(data_dir, self._VALID_FILE)}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={"filepath": os.path.join(data_dir, self._TEST_FILE)}, | |
), | |
] | |
def _generate_examples(self, filepath): | |
"""Yields examples.""" | |
with open(filepath, encoding="utf-8") as f: | |
for id_, row in enumerate(f): | |
data = json.loads(row) | |
yield id_, { | |
"question_id": data["question_id"], | |
"article_id": data["article_id"], | |
"title": data["title"], | |
"context": data["context"], | |
"question": data["question"], | |
"answers": { | |
"text": data["answers"]["text"], | |
"answer_start": data["answers"]["answer_start"], | |
"answer_end": data["answers"]["answer_end"], | |
}, | |
} | |