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upload hubscripts/genia_relation_corpus_hub.py to hub from bigbio repo

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  1. genia_relation_corpus.py +217 -0
genia_relation_corpus.py ADDED
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+ # coding=utf-8
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+ # Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+
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+ """
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+ The extraction of various relations stated to hold between biomolecular entities is one of the most frequently
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+ addressed information extraction tasks in domain studies. Typical relation extraction targets involve protein-protein
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+ interactions or gene regulatory relations. However, in the GENIA corpus, such associations involving change in the
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+ state or properties of biomolecules are captured in the event annotation.
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+
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+ The GENIA corpus relation annotation aims to complement the event annotation of the corpus by capturing (primarily)
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+ static relations, relations such as part-of that hold between entities without (necessarily) involving change.
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+ """
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+
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+ import os
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+ from pathlib import Path
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+ from typing import Dict, List, Tuple
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+
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+ import datasets
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+
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+ from .bigbiohub import kb_features
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+ from .bigbiohub import BigBioConfig
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+ from .bigbiohub import Tasks
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+
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+ _LANGUAGES = ['English']
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+ _PUBMED = True
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+ _LOCAL = False
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+ _CITATION = """\
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+ @inproceedings{pyysalo-etal-2009-static,
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+ title = "Static Relations: a Piece in the Biomedical Information Extraction Puzzle",
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+ author = "Pyysalo, Sampo and
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+ Ohta, Tomoko and
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+ Kim, Jin-Dong and
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+ Tsujii, Jun{'}ichi",
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+ booktitle = "Proceedings of the {B}io{NLP} 2009 Workshop",
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+ month = jun,
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+ year = "2009",
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+ address = "Boulder, Colorado",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/W09-1301",
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+ pages = "1--9",
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+ }
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+
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+ @article{article,
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+ author = {Ohta, Tomoko and Pyysalo, Sampo and Kim, Jin-Dong and Tsujii, Jun'ichi},
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+ year = {2010},
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+ month = {10},
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+ pages = {917-28},
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+ title = {A reevaluation of biomedical named entity - term relations},
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+ volume = {8},
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+ journal = {Journal of bioinformatics and computational biology},
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+ doi = {10.1142/S0219720010005014}
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+ }
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+
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+ @MISC{Hoehndorf_applyingontology,
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+ author = {Robert Hoehndorf and Axel-cyrille Ngonga Ngomo and Sampo Pyysalo and Tomoko Ohta and Anika Oellrich and
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+ Dietrich Rebholz-schuhmann},
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+ title = {Applying ontology design patterns to the implementation of relations in GENIA},
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+ year = {}
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+ }
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+ """
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+
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+ _DATASETNAME = "genia_relation_corpus"
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+ _DISPLAYNAME = "GENIA Relation Corpus"
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+
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+ _DESCRIPTION = """\
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+ The extraction of various relations stated to hold between biomolecular entities is one of the most frequently
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+ addressed information extraction tasks in domain studies. Typical relation extraction targets involve protein-protein
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+ interactions or gene regulatory relations. However, in the GENIA corpus, such associations involving change in the
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+ state or properties of biomolecules are captured in the event annotation.
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+
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+ The GENIA corpus relation annotation aims to complement the event annotation of the corpus by capturing (primarily)
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+ static relations, relations such as part-of that hold between entities without (necessarily) involving change.
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+ """
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+
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+ _HOMEPAGE = "http://www.geniaproject.org/genia-corpus/relation-corpus"
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+
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+ _LICENSE = 'GENIA Project License for Annotated Corpora'
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+
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+ _URLS = {
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+ _DATASETNAME: {
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+ "train": "http://www.nactem.ac.uk/GENIA/current/GENIA-corpus/Relation/GENIA_relation_annotation_training_data.tar.gz",
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+ "validation": "http://www.nactem.ac.uk/GENIA/current/GENIA-corpus/Relation/GENIA_relation_annotation_development_data.tar.gz",
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+ "test": "http://www.nactem.ac.uk/GENIA/current/GENIA-corpus/Relation/GENIA_relation_annotation_test_data.tar.gz",
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+ },
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+ }
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+
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+ _SUPPORTED_TASKS = [Tasks.RELATION_EXTRACTION]
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+
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+ _SOURCE_VERSION = "1.0.0"
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+
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+ _BIGBIO_VERSION = "1.0.0"
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+
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+
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+ class GeniaRelationCorpusDataset(datasets.GeneratorBasedBuilder):
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+ """GENIA Relation corpus."""
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+
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+ SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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+ BIGBIO_VERSION = datasets.Version(_BIGBIO_VERSION)
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+
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+ BUILDER_CONFIGS = [
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+ BigBioConfig(
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+ name="genia_relation_corpus_source",
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+ version=SOURCE_VERSION,
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+ description="genia_relation_corpus source schema",
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+ schema="source",
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+ subset_id="genia_relation_corpus",
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+ ),
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+ BigBioConfig(
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+ name="genia_relation_corpus_bigbio_kb",
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+ version=BIGBIO_VERSION,
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+ description="genia_relation_corpus BigBio schema",
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+ schema="bigbio_kb",
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+ subset_id="genia_relation_corpus",
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+ ),
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+ ]
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+
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+ DEFAULT_CONFIG_NAME = "genia_relation_corpus_source"
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+
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+ def _info(self) -> datasets.DatasetInfo:
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+ if self.config.schema == "source":
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+ features = datasets.Features(
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+ {
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+ "id": datasets.Value("string"),
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+ "document_id": datasets.Value("string"),
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+ "text": datasets.Value("string"),
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+ "text_bound_annotations": [ # T line in brat, e.g. type or event trigger
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+ {
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+ "offsets": datasets.Sequence([datasets.Value("int32")]),
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+ "text": datasets.Sequence(datasets.Value("string")),
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+ "type": datasets.Value("string"),
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+ "id": datasets.Value("string"),
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+ }
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+ ],
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+ "relations": [ # R line in brat
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+ {
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+ "id": datasets.Value("string"),
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+ "head": {
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+ "ref_id": datasets.Value("string"),
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+ "role": datasets.Value("string"),
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+ },
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+ "tail": {
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+ "ref_id": datasets.Value("string"),
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+ "role": datasets.Value("string"),
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+ },
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+ "type": datasets.Value("string"),
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+ }
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+ ],
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+ "equivalences": [ # Equiv line in brat
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+ {
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+ "id": datasets.Value("string"),
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+ "ref_ids": datasets.Sequence(datasets.Value("string")),
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+ }
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+ ],
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+ },
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+ )
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+
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+ elif self.config.schema == "bigbio_kb":
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+ features = kb_features
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+
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=features,
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+ homepage=_HOMEPAGE,
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+ license=str(_LICENSE),
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager) -> List[datasets.SplitGenerator]:
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+ """Returns SplitGenerators."""
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+ urls = _URLS[_DATASETNAME]
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+ data_dir = dl_manager.download_and_extract(urls)
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+ return [
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+ datasets.SplitGenerator(
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+ name=split,
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+ gen_kwargs={
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+ "data_dir": data_dir[split],
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+ },
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+ )
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+ for split in [
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+ datasets.Split.TRAIN,
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+ datasets.Split.VALIDATION,
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+ datasets.Split.TEST,
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+ ]
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+ ]
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+
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+ def _generate_examples(self, data_dir) -> Tuple[int, Dict]:
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+ """Yields examples as (key, example) tuples."""
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+ for dirpath, _, filenames in os.walk(data_dir):
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+ for guid, filename in enumerate(filenames):
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+ if filename.endswith(".txt"):
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+ txt_file_path = Path(dirpath, filename)
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+ if self.config.schema == "source":
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+ example = parsing.parse_brat_file(
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+ txt_file_path, annotation_file_suffixes=[".a1", ".rel"]
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+ )
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+ example["id"] = str(guid)
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+ for key in ["events", "attributes", "normalizations"]:
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+ del example[key]
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+ yield guid, example
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+ elif self.config.schema == "bigbio_kb":
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+ example = parsing.brat_parse_to_bigbio_kb(
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+ parsing.parse_brat_file(txt_file_path)
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+ )
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+ example["id"] = str(guid)
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+ yield guid, example