snli_cs.py

import os
import pathlib
from typing import overload
import datasets
import json

from datasets.info import DatasetInfo

_VERSION = "1.0.0"

_URL= "https://fcheck.fel.cvut.cz/downloads/NLI/snli_1.0_cs_google_translate/"

_URLS = {
    "train": _URL + "snli_1.0_train.jsonl",
    "validation": _URL + "snli_1.0_dev.jsonl",
    "test": _URL + "snli_1.0_test.jsonl"
}

_DESCRIPTION = """\
TODO: Snli_cs is a Czech translation of the Stanford NLI dataset 
"""

_CITATION = """\
todo
"""

_LABEL_CONVERSION = {
    "-": "NOT ENOUGH INFO",
    "neutral": "NOT ENOUGH INFO",
    "entailment": "SUPPORTS",
    "contradiction": "REFUTES"
}

datasets.utils.version.Version
class SnliCs(datasets.GeneratorBasedBuilder):
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("string"),
                    "label": datasets.ClassLabel(names=["REFUTES", "NOT ENOUGH INFO", "SUPPORTS"]),
                    # datasets.features.Sequence({"text": datasets.Value("string"),"answer_start": datasets.Value("int32"),})
                    "evidence": datasets.Value("string"),
                    "claim": datasets.Value("string"),
                }
            ),
            # No default supervised_keys (as we have to pass both question
            # and context as input).
            supervised_keys=None,
            version=_VERSION,
            homepage="https://fcheck.fel.cvut.cz/dataset/",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager: datasets.DownloadManager):
        downloaded_files = dl_manager.download_and_extract(_URLS)

        return [
            datasets.SplitGenerator(datasets.Split.TRAIN, {
                "filepath": downloaded_files["train"]
            }),
            datasets.SplitGenerator(datasets.Split.VALIDATION, {
                "filepath": downloaded_files["validation"]
            }),
            datasets.SplitGenerator(datasets.Split.TEST, {
                "filepath": downloaded_files["test"]
            }),
        ]

    def _generate_examples(self, filepath):
        """This function returns the examples in the raw (text) form."""
        key = 0
        with open(filepath, encoding="utf-8") as f:
            for line in f:
                datapoint = json.loads(line)
                yield key, {
                    "id": datapoint["pairID"],
                    "evidence": datapoint["sentence1"],
                    "claim": datapoint["sentence2"],
                    "label": _LABEL_CONVERSION[datapoint["gold_label"]]
                }
                key += 1