nlpcc_stance.py

# 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 = """\
"""

_DESCRIPTION = """\
"""

_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("nlpcc_taska.csv")
        test_text  = dl_manager.download_and_extract("NLPCC2016_Stance_Detection_Task_A_Testdata.tsv")
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN,      gen_kwargs={"filepath": train_text, "split": "train"}),
            datasets.SplitGenerator(name=datasets.Split.TEST,       gen_kwargs={"filepath": test_text,  "split": "test"}),
        ]

    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:
                print(f"At iteration: {guid}")
                instance["target"] = instance.pop("TARGET")
                instance["text"] = instance.pop("TEXT")
                instance["stance"] = instance.pop("STANCE")
                instance['id'] = str(guid)
                yield guid, instance
                guid += 1