| import json |
| from typing import List |
|
|
| import datasets |
|
|
| _VERSION = "1.0.0" |
|
|
| _CITATION = """\ |
| @inproceedings{decao2021autoregressive, |
| author = {Nicola {De Cao} and |
| Gautier Izacard and |
| Sebastian Riedel and |
| Fabio Petroni}, |
| title = {Autoregressive Entity Retrieval}, |
| booktitle = {9th International Conference on Learning Representations, {ICLR} 2021, |
| Virtual Event, Austria, May 3-7, 2021}, |
| publisher = {OpenReview.net}, |
| year = {2021}, |
| url = {https://openreview.net/forum?id=5k8F6UU39V}, |
| }""" |
|
|
|
|
| class EntityDisambiguationConfig(datasets.BuilderConfig): |
| """BuilderConfig for EntityDisambiguation.""" |
|
|
| def __init__(self, **kwargs): |
| """BuilderConfig for EntityDisambiguation. |
| |
| Args: |
| **kwargs: keyword arguments forwarded to super. |
| """ |
| super(EntityDisambiguationConfig, self).__init__(**kwargs) |
|
|
| self.features = datasets.Features( |
| { |
| "id": datasets.Value("string"), |
| "input": datasets.Value("string"), |
| "meta": { |
| "left_context": datasets.Value("string"), |
| "mention": datasets.Value("string"), |
| "right_context": datasets.Value("string"), |
| }, |
| "candidates": datasets.features.Sequence(datasets.Value("string")), |
| "answer": datasets.Value("string") |
| } |
| ) |
|
|
|
|
| class EntityDisambiguation(datasets.GeneratorBasedBuilder): |
| """Entity Disambiguation dataset.""" |
|
|
| VERSION = datasets.Version(_VERSION) |
|
|
| BUILDER_CONFIGS = [ |
| EntityDisambiguationConfig(name="ace2004", version=VERSION, description="ACE2004 dataset"), |
| EntityDisambiguationConfig(name="aida", version=VERSION, description="AIDA dataset"), |
| EntityDisambiguationConfig(name="aquaint", version=VERSION, description="AQUAINT dataset"), |
| EntityDisambiguationConfig(name="blink", version=VERSION, description="BLINK dataset"), |
| EntityDisambiguationConfig(name="clueweb", version=VERSION, description="CWEB dataset"), |
| EntityDisambiguationConfig(name="msnbc", version=VERSION, description="MSNBC dataset"), |
| EntityDisambiguationConfig(name="wiki", version=VERSION, description="WIKI dataset"), |
| ] |
|
|
| def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
| """Returns SplitGenerators.""" |
|
|
| if self.config.name == "blink": |
| available_splits = ["train", "dev"] |
| elif self.config.name == "aida": |
| available_splits = ["train", "dev", "test"] |
| else: |
| available_splits = ["test"] |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=split, |
| gen_kwargs={ |
| "filepath": dl_manager.download_and_extract( |
| f"http://dl.fbaipublicfiles.com/{'KILT' if self.config.name.lower() == 'blink' else 'GENRE'}" |
| f"/{self.config.name.lower()}-{split}-kilt.jsonl"), |
| "split": split, |
| }, |
| ) |
| for split in available_splits |
| ] |
|
|
| def _info(self) -> datasets.DatasetInfo: |
| return datasets.DatasetInfo(description="Entity Disambiguation dataset", features=self.config.features, |
| citation=_CITATION) |
|
|
| def _generate_examples(self, filepath: str, split: str): |
| with open(filepath, encoding="utf-8") as f: |
| for line in f: |
| row = json.loads(line) |
| row["answer"] = row["output"][0]["answer"] |
|
|
| del row["output"] |
|
|
| yield row["id"], row |
|
|
