Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-label-classification
Languages:
Hindi
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
other
Source Datasets:
original
License:
File size: 3,618 Bytes
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# 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.
"""TODO: Add a description here."""
import json
import datasets
_CITATION = """\
@inproceedings{swapnil2020,
title={An Annotated Dataset of Discourse Modes in Hindi Stories},
author={Swapnil Dhanwal, Hritwik Dutta, Hitesh Nankani, Nilay Shrivastava, Yaman Kumar, Junyi Jessy Li, Debanjan Mahata, Rakesh Gosangi, Haimin Zhang, Rajiv Ratn Shah, Amanda Stent},
booktitle={Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
volume={12},
pages={1191–1196},
year={2020}
"""
_DESCRIPTION = """\
The Hindi Discourse Analysis dataset is a corpus for analyzing discourse modes present in its sentences.
It contains sentences from stories written by 11 famous authors from the 20th Century.
4-5 stories by each author have been selected which were available in the public domain resulting
in a collection of 53 stories. Most of these short stories were originally written in Hindi
but some of them were written in other Indian languages and later translated to Hindi.
"""
_DOWNLOAD_URL = "https://raw.githubusercontent.com/midas-research/hindi-discourse/master/discourse_dataset.json"
class HindiDiscourse(datasets.GeneratorBasedBuilder):
"""Hindi Discourse Dataset - dataset of discourse modes in Hindi stories."""
VERSION = datasets.Version("1.0.0")
def _info(self):
# This method pecifies the datasets.DatasetInfo object which contains informations and typings for the dataset
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
features=datasets.Features(
{
"Story_no": datasets.Value("int32"),
"Sentence": datasets.Value("string"),
"Discourse Mode": datasets.ClassLabel(
names=["Argumentative", "Descriptive", "Dialogue", "Informative", "Narrative", "Other"]
),
}
),
supervised_keys=None,
# Homepage of the dataset for documentation
homepage="https://github.com/midas-research/hindi-discourse",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
dataset_path = dl_manager.download_and_extract(_DOWNLOAD_URL)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": dataset_path}),
]
def _generate_examples(self, filepath):
"""Yields examples."""
with open(filepath, encoding="utf-8") as f:
hindiDiscourse = json.load(f)
for sentence, rowData in hindiDiscourse.items():
yield sentence, {
"Story_no": rowData["Story_no"],
"Sentence": rowData["Sentence"],
"Discourse Mode": rowData["Discourse Mode"],
}
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