Datasets:

Divyanshu
/

IE_SemParse

	# coding=utf-8


	# Lint as: python3
	"""IE-SemParse: The Inter-Bilingual Semantic Parsing for Indic Languages."""


	import os
	import json

	import pandas as pd

	import datasets

	from datasets import DownloadManager


	_CITATION = """\
	@misc{aggarwal2023evaluating,
	title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages},
	author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
	year={2023},
	eprint={2304.13005},
	archivePrefix={arXiv},
	primaryClass={cs.CL}
	}
	"""

	_DESCRIPTION = """\
	IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
	"""

	_LANGUAGES = (
	'hi',
	'bn',
	'mr',
	'as',
	'ta',
	'te',
	'or',
	'ml',
	'pa',
	'gu',
	'kn'
	)



	_DATASETS = (
	"IE-mTOP",
	"IE-ATIS",
	"IE-multilingualTOP"
	)

	mapping = {"IE-mTOP": "itop",
	"IE-ATIS": "indic-atis",
	"IE-multilingualTOP": "indic-TOP"}


	_URL = "https://huggingface.co/datasets/Divyanshu/IE_SemParse/resolve/main/"


	class IE_SemParseConfig(datasets.BuilderConfig):
	"""BuilderConfig for IE-SemParse."""

	def __init__(self, dataset: str, language: str, **kwargs):
	"""BuilderConfig for IE-SemParse.

	Args:
	language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
	**kwargs: keyword arguments forwarded to super.
	"""
	super(IE_SemParseConfig, self).__init__(**kwargs)

	self.dataset = dataset
	self.language = language
	self.languages = _LANGUAGES
	self.datasets = _DATASETS

	self._URLS = [os.path.join(
	_URL, "unfiltered_data", mapping[dataset], f"{language}.json")]


	class IE_SemParse(datasets.GeneratorBasedBuilder):
	"""IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""

	VERSION = datasets.Version("1.0.0", "")
	BUILDER_CONFIG_CLASS = IE_SemParseConfig
	BUILDER_CONFIGS = [
	IE_SemParseConfig(
	name=f"{dataset}_{language}",
	language=language,
	dataset=dataset,
	version=datasets.Version("1.0.0", ""),
	description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
	)
	for language, dataset in zip(_LANGUAGES, _DATASETS)
	]

	def _info(self):
	dl_manager = datasets.DownloadManager()

	urls_to_download = self.config._URLS

	filepath = dl_manager.download_and_extract(urls_to_download)[0]

	with open(filepath, "r") as f:
	data = json.load(f)

	features = datasets.Features(
	{k: datasets.Value("string") for k in data['train'][0].keys()}
	)

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	# No default supervised_keys (as we have to pass both premise
	# and hypothesis as input).
	supervised_keys=None,
	homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	urls_to_download = self.config._URLS

	downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"split_key": "train",
	"filepath": downloaded_file,
	"data_format": "IE-SemParse"
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"split_key": "test",
	"filepath": downloaded_file,
	"data_format": "IE-SemParse"
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"split_key": "validation",
	"filepath": downloaded_file,
	"data_format": "IE-SemParse"
	},
	),
	]

	def _generate_examples(self, data_format, split_key, filepath):
	"""This function returns the examples in the raw (text) form."""

	with open(filepath, "r") as f:
	data = json.load(f)
	data = data[split_key]

	for idx, row in enumerate(data):
	yield idx, {
	k: v for k, v in row.items()
	}