Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-analysis
Languages:
Chinese
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
License:
| # Copyright 2022 Mads Kongsbak and Leon Derczynski | |
| # | |
| # 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. | |
| """NLPCC Shared Task 4, Stance Detection in Chinese Microblogs (Task A)""" | |
| import csv | |
| import json | |
| import os | |
| import datasets | |
| _CITATION = """\ | |
| @incollection{xu2016overview, | |
| title={Overview of nlpcc shared task 4: Stance detection in chinese microblogs}, | |
| author={Xu, Ruifeng and Zhou, Yu and Wu, Dongyin and Gui, Lin and Du, Jiachen and Xue, Yun}, | |
| booktitle={Natural language understanding and intelligent applications}, | |
| pages={907--916}, | |
| year={2016}, | |
| publisher={Springer} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| This is a stance prediction dataset in Chinese. | |
| The data is that from a shared task, stance detection in Chinese microblogs, in NLPCC-ICCPOL 2016. It covers Task A, a mandatory supervised task which detects stance towards five targets of interest with given labeled data. | |
| """ | |
| _HOMEPAGE = "" | |
| _LICENSE = "cc-by-4.0" | |
| class NLPCCConfig(datasets.BuilderConfig): | |
| def __init__(self, **kwargs): | |
| super(NLPCCConfig, self).__init__(**kwargs) | |
| class NLPCCStance(datasets.GeneratorBasedBuilder): | |
| """The NLPCC Shared Task 4 dataset regarding Stance Detection in Chinese Microblogs (Task A)""" | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIGS = [ | |
| NLPCCConfig(name="task_a", version=VERSION, description="Task A, the supervised learning task."), | |
| ] | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "id": datasets.Value("string"), | |
| "target": datasets.Value("string"), | |
| "text": datasets.Value("string"), | |
| "stance": datasets.features.ClassLabel( | |
| names=[ | |
| "AGAINST", | |
| "FAVOR", | |
| "NONE", | |
| ] | |
| ) | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| train_text = dl_manager.download_and_extract("taska_train.csv") | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_text, "split": "train"}), | |
| ] | |
| def _generate_examples(self, filepath, split): | |
| with open(filepath, encoding="utf-8") as f: | |
| reader = csv.DictReader(f, delimiter=",") | |
| guid = 0 | |
| for instance in reader: | |
| instance["target"] = instance.pop("target") | |
| instance["text"] = instance.pop("text") | |
| instance["stance"] = instance.pop("stance") | |
| instance['id'] = str(guid) | |
| yield guid, instance | |
| guid += 1 |