wiki-entity-similarity.py

import datasets

from dataclasses import dataclass
import csv

_DESCRIPTION = '''WES: Learning Semantic Similarity from 6M Names for 1M Entities'''
_CITE = '''\
@inproceedings{exr0n2022WES
    author={Exr0n},
    title={WES: Learning Semantic Similarity from 6M Names for 1M Entities},
    year={2022}
}
'''

@dataclass
class WikiEntitySimilarityConfig(datasets.BuilderConfig):
    """BuilderConfig for CSV."""
    threshhold: int = None
    path: str = None

class WikiEntitySimilarity(datasets.GeneratorBasedBuilder):
    """WES: Learning semantic similarity from 6M names for 1M entities"""
    BUILDER_CONFIG_CLASS = WikiEntitySimilarityConfig
    BUILDER_CONFIGS = [
        WikiEntitySimilarityConfig(
            name='2008thresh5',
            description='min 5 inbound links, lowest quality',
            threshhold=5,
            path="https://huggingface.co/datasets/Exr0n/wiki-entity-similarity/resolve/main/link_synonyms-2018-thresh_5.csv"
        ),
        WikiEntitySimilarityConfig(
            name='2008thresh10',
            description='min 10 inbound links, medium quality',
            threshhold=10,
            path="https://huggingface.co/datasets/Exr0n/wiki-entity-similarity/resolve/main/link_synonyms-2018-thresh_10.csv"
        ),
        WikiEntitySimilarityConfig(
            name='2008thresh20',
            description='min 20 inbound links, high quality',
            threshhold=20,
            path="https://huggingface.co/datasets/Exr0n/wiki-entity-similarity/resolve/main/link_synonyms-2018-thresh_20.csv"
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    'article': datasets.Value('string'),
                    'link_text': datasets.Value('string'),
                }
            ),
            citation=_CITE,
            homepage="https://github.com/Exr0nProjects/wiki-entity-similarity",
        )

    def _split_generators(self, dl_manager):
        filepath = dl_manager.download(self.config.path)
        return [ datasets.SplitGenerator(name=datasets.Split.ALL,
                                         gen_kwargs={ 'filepath': filepath }) ]

    def _generate_examples(self, filepath):
        with open(filepath, 'r') as rf:
            reader = csv.DictReader(rf)
            for i, row in enumerate(reader):
                yield i, row