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sredfm.py

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+# Some code referenced from https://huggingface.co/datasets/Babelscape/SREDFM/blob/main/SREDFM.py
+
+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": [],
+                    }