| |
|
|
| from pathlib import Path |
| from typing import Dict, List, Tuple |
|
|
| import datasets |
| import jsonlines |
|
|
| from seacrowd.utils import schemas |
| from seacrowd.utils.configs import SEACrowdConfig |
| from seacrowd.utils.constants import Licenses, Tasks |
|
|
| _CITATION = """\ |
| @inproceedings{huguet-cabot-et-al-2023-redfm-dataset, |
| title = "RED$^{\rm FM}$: a Filtered and Multilingual Relation Extraction Dataset", |
| author = "Huguet Cabot, Pere-Lluís and Tedeschi, Simone and Ngonga Ngomo, Axel-Cyrille and |
| Navigli, Roberto", |
| booktitle = "Proc. of the 61st Annual Meeting of the Association for Computational Linguistics: ACL 2023", |
| month = jul, |
| year = "2023", |
| address = "Toronto, Canada", |
| publisher = "Association for Computational Linguistics", |
| url = "https://arxiv.org/abs/2306.09802", |
| } |
| """ |
|
|
| _DATASETNAME = "sredfm" |
|
|
|
|
| _DESCRIPTION = """\ |
| SREDFM is an automatically annotated dataset for relation extraction task covering 18 languages, 400 relation types, 13 entity types, totaling more than 40 million triplet instances. SREDFM includes Vietnamnese. |
| """ |
|
|
| _HOMEPAGE = "https://github.com/babelscape/rebel" |
|
|
| _LANGUAGES = ["vie"] |
|
|
| _LICENSE = Licenses.CC_BY_SA_4_0.value |
|
|
| _LOCAL = False |
|
|
| _URLS = { |
| "train": "https://huggingface.co/datasets/Babelscape/SREDFM/resolve/main/data/train.vi.jsonl", |
| "dev": "https://huggingface.co/datasets/Babelscape/SREDFM/resolve/main/data/dev.vi.jsonl", |
| "test": "https://huggingface.co/datasets/Babelscape/SREDFM/resolve/main/data/test.vi.jsonl", |
| "relations_url": "https://huggingface.co/datasets/Babelscape/SREDFM/raw/main/relations.tsv", |
| } |
|
|
| _SUPPORTED_TASKS = [Tasks.RELATION_EXTRACTION] |
|
|
| _SOURCE_VERSION = "1.0.0" |
|
|
| _SEACROWD_VERSION = "2024.06.20" |
|
|
|
|
| class SREDFMDataset(datasets.GeneratorBasedBuilder): |
| """SREDFM is an automatically annotated dataset for relation extraction task. |
| Relation Extraction (RE) is a task that identifies relationships between entities in a text, |
| enabling the acquisition of relational facts and bridging the gap between natural language |
| and structured knowledge. SREDFM covers 400 relation types, 13 entity types, |
| totaling more than 40 million triplet instances.""" |
|
|
| SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) |
| SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION) |
|
|
| BUILDER_CONFIGS = [ |
| SEACrowdConfig( |
| name=f"{_DATASETNAME}_source", |
| version=SOURCE_VERSION, |
| description=f"{_DATASETNAME} source schema", |
| schema="source", |
| subset_id=f"{_DATASETNAME}", |
| ), |
| SEACrowdConfig( |
| name=f"{_DATASETNAME}_seacrowd_kb", |
| version=SEACROWD_VERSION, |
| description=f"{_DATASETNAME} SEACrowd schema", |
| schema="seacrowd_kb", |
| subset_id=f"{_DATASETNAME}", |
| ), |
| ] |
|
|
| DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source" |
|
|
| def _info(self) -> datasets.DatasetInfo: |
| if self.config.schema == "source": |
| features = datasets.Features( |
| { |
| "docid": datasets.Value("string"), |
| "title": datasets.Value("string"), |
| "uri": datasets.Value("string"), |
| "text": datasets.Value("string"), |
| "entities": [ |
| { |
| "uri": datasets.Value(dtype="string"), |
| "surfaceform": datasets.Value(dtype="string"), |
| "type": datasets.Value(dtype="string"), |
| "start": datasets.Value(dtype="int32"), |
| "end": datasets.Value(dtype="int32"), |
| } |
| ], |
| "relations": [ |
| { |
| "subject": datasets.Value(dtype="int32"), |
| "predicate": datasets.Value(dtype="string"), |
| "object": datasets.Value(dtype="int32"), |
| } |
| ], |
| } |
| ) |
|
|
| elif self.config.schema == "seacrowd_kb": |
| features = schemas.kb_features |
|
|
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=features, |
| homepage=_HOMEPAGE, |
| license=_LICENSE, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
| """Returns SplitGenerators.""" |
| data_dir = dl_manager.download_and_extract(_URLS) |
|
|
| relation_names = dict() |
| relation_path = data_dir["relations_url"] |
| with open(relation_path, encoding="utf-8") as f: |
| for row in f: |
| rel_code, rel_name, _, _ = row.strip().split("\t") |
| relation_names[rel_code] = rel_name |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={"filepath": data_dir["train"], "relation_names": relation_names}, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, |
| gen_kwargs={"filepath": data_dir["test"], "relation_names": relation_names}, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.VALIDATION, |
| gen_kwargs={"filepath": data_dir["dev"], "relation_names": relation_names}, |
| ), |
| ] |
|
|
| def _generate_examples(self, filepath: Path, relation_names: dict) -> Tuple[int, Dict]: |
| """Yields examples as (key, example) tuples.""" |
|
|
| if self.config.schema == "source": |
| with jsonlines.open(filepath) as f: |
| skip = set() |
| for example in f.iter(): |
| if example["docid"] in skip: |
| continue |
| skip.add(example["docid"]) |
|
|
| entities = [] |
| for entity in example["entities"]: |
| entities.append( |
| { |
| "uri": entity["uri"], |
| "surfaceform": entity["surfaceform"], |
| "start": entity["boundaries"][0], |
| "end": entity["boundaries"][1], |
| "type": entity["type"], |
| } |
| ) |
|
|
| relations = [] |
| for relation in example["relations"]: |
| if relation["predicate"]["uri"] not in relation_names or relation["confidence"] <= 0.75: |
| continue |
|
|
| relations.append( |
| { |
| "subject": entities.index( |
| { |
| "uri": relation["subject"]["uri"], |
| "surfaceform": relation["subject"]["surfaceform"], |
| "start": relation["subject"]["boundaries"][0], |
| "end": relation["subject"]["boundaries"][1], |
| "type": relation["subject"]["type"], |
| } |
| ), |
| "predicate": relation_names[relation["predicate"]["uri"]], |
| "object": entities.index( |
| { |
| "uri": relation["object"]["uri"], |
| "surfaceform": relation["object"]["surfaceform"], |
| "start": relation["object"]["boundaries"][0], |
| "end": relation["object"]["boundaries"][1], |
| "type": relation["object"]["type"], |
| } |
| ), |
| } |
| ) |
|
|
| if len(relations) == 0: |
| continue |
|
|
| yield example["docid"], { |
| "docid": example["docid"], |
| "title": example["title"], |
| "uri": example["uri"], |
| "text": example["text"], |
| "entities": entities, |
| "relations": relations, |
| } |
|
|
| elif self.config.schema == "seacrowd_kb": |
| with jsonlines.open(filepath) as f: |
| skip = set() |
| i = 0 |
| for example in f.iter(): |
| if example["docid"] in skip: |
| continue |
| skip.add(example["docid"]) |
|
|
| i += 1 |
| processed_text = example["text"].replace("\n", " ") |
| passages = [ |
| { |
| "id": f"{i}-{example['uri']}", |
| "type": "text", |
| "text": [processed_text], |
| "offsets": [[0, len(processed_text)]], |
| } |
| ] |
|
|
| entities = [] |
| for entity in example["entities"]: |
| entities.append( |
| { |
| "id": entity["uri"], |
| "type": entity["type"], |
| "text": [entity["surfaceform"]], |
| "offsets": [entity["boundaries"]], |
| "normalized": {"db_name": "", "db_id": ""}, |
| } |
| ) |
|
|
| relations = [] |
| for relation in example["relations"]: |
| if relation["predicate"]["uri"] not in relation_names or relation["confidence"] <= 0.75: |
| continue |
|
|
| i += 1 |
| sub = relation["subject"] |
| pred = relation["predicate"] |
| obj = relation["object"] |
| relations.append( |
| { |
| "id": f"{i}-{sub['uri']}-{pred['uri']}-{obj['uri']}", |
| "type": relation_names[pred["uri"]], |
| "arg1_id": str( |
| entities.index( |
| { |
| "id": sub["uri"], |
| "type": sub["type"], |
| "text": [sub["surfaceform"]], |
| "offsets": [sub["boundaries"]], |
| "normalized": {"db_name": "", "db_id": ""}, |
| } |
| ) |
| ), |
| "arg2_id": str( |
| entities.index( |
| { |
| "id": obj["uri"], |
| "type": obj["type"], |
| "text": [obj["surfaceform"]], |
| "offsets": [obj["boundaries"]], |
| "normalized": {"db_name": "", "db_id": ""}, |
| } |
| ) |
| ), |
| "normalized": {"db_name": "", "db_id": ""}, |
| } |
| ) |
|
|
| for entity in entities: |
| i += 1 |
| entity["id"] = f"{i}-{entity['id']}" |
|
|
| if len(relations) == 0: |
| continue |
|
|
| yield example["docid"], { |
| "id": example["docid"], |
| "passages": passages, |
| "entities": entities, |
| "relations": relations, |
| "events": [], |
| "coreferences": [], |
| } |
|
|
