upload hubscripts/bionlp_shared_task_2009_hub.py to hub from bigbio repo

bionlp_shared_task_2009.py

@@ -0,0 +1,231 @@
+# coding=utf-8
+# Copyright 2022 The HuggingFace Datasets Authors and
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from pathlib import Path
+from typing import Dict, List
+
+import datasets
+
+from .bigbiohub import kb_features
+from .bigbiohub import BigBioConfig
+from .bigbiohub import Tasks
+
+_LANGUAGES = ['English']
+_PUBMED = True
+_LOCAL = False
+_CITATION = """\
+@inproceedings{kim-etal-2009-overview,
+    title = "Overview of {B}io{NLP}{'}09 Shared Task on Event Extraction",
+    author = "Kim, Jin-Dong  and
+      Ohta, Tomoko  and
+      Pyysalo, Sampo  and
+      Kano, Yoshinobu  and
+      Tsujii, Jun{'}ichi",
+    booktitle = "Proceedings of the {B}io{NLP} 2009 Workshop Companion Volume for Shared Task",
+    month = jun,
+    year = "2009",
+    address = "Boulder, Colorado",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/W09-1401",
+    pages = "1--9",
+}
+"""
+
+_DATASETNAME = "bionlp_shared_task_2009"
+_DISPLAYNAME = "BioNLP 2009"
+
+_DESCRIPTION = """\
+The BioNLP Shared Task 2009 was organized by GENIA Project and its corpora were curated based
+on the annotations of the publicly available GENIA Event corpus and an unreleased (blind) section
+of the GENIA Event corpus annotations, used for evaluation.
+"""
+
+_HOMEPAGE = "http://www.geniaproject.org/shared-tasks/bionlp-shared-task-2009"
+
+_LICENSE = 'GENIA Project License for Annotated Corpora'
+
+_URL_BASE = "http://www.nactem.ac.uk/GENIA/current/Shared-tasks/BioNLP-ST-2009/"
+_URLS = {
+    _DATASETNAME: {
+        "train": _URL_BASE + "bionlp09_shared_task_training_data_rev2.tar.gz",
+        "test": _URL_BASE
+        + "bionlp09_shared_task_test_data_without_gold_annotation.tar.gz",
+        "dev": _URL_BASE + "bionlp09_shared_task_development_data_rev1.tar.gz",
+    },
+}
+
+_SUPPORTED_TASKS = [
+    Tasks.NAMED_ENTITY_RECOGNITION,
+    Tasks.EVENT_EXTRACTION,
+    Tasks.COREFERENCE_RESOLUTION,
+]
+
+_SOURCE_VERSION = "1.0.0"
+
+_BIGBIO_VERSION = "1.0.0"
+
+# https://2011.bionlp-st.org/bionlp-shared-task-2011/genia-event-extraction-genia
+
+
+class BioNLPSharedTask2009(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    BIGBIO_VERSION = datasets.Version(_BIGBIO_VERSION)
+
+    BUILDER_CONFIGS = [
+        BigBioConfig(
+            name="bionlp_shared_task_2009_source",
+            version=SOURCE_VERSION,
+            description="bionlp_shared_task_2009 source schema",
+            schema="source",
+            subset_id="bionlp_shared_task_2009",
+        ),
+        BigBioConfig(
+            name="bionlp_shared_task_2009_bigbio_kb",
+            version=BIGBIO_VERSION,
+            description="bionlp_shared_task_2009 BigBio schema",
+            schema="bigbio_kb",
+            subset_id="bionlp_shared_task_2009",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "bionlp_shared_task_2009_source"
+
+    _ROLE_MAPPING = {
+        "Theme2": "Theme",
+        "Theme3": "Theme",
+        "Theme4": "Theme",
+        "Site2": "Site",
+    }
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "document_id": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "text_bound_annotations": [
+                        {
+                            "id": datasets.Value("string"),
+                            "offsets": [[datasets.Value("int64")]],
+                            "text": [datasets.Value("string")],
+                            "type": datasets.Value("string"),
+                        }
+                    ],
+                    "events": [
+                        {
+                            "arguments": [
+                                {
+                                    "ref_id": datasets.Value("string"),
+                                    "role": datasets.Value("string"),
+                                }
+                            ],
+                            "id": datasets.Value("string"),
+                            "trigger": datasets.Value("string"),
+                            "type": datasets.Value("string"),
+                        }
+                    ],
+                    "relations": [
+                        {
+                            "id": datasets.Value("string"),
+                            "type": datasets.Value("string"),
+                            "arg1_id": datasets.Value("string"),
+                            "arg2_id": datasets.Value("string"),
+                            "normalized": [
+                                {
+                                    "db_name": datasets.Value("string"),
+                                    "db_id": datasets.Value("string"),
+                                }
+                            ],
+                        }
+                    ],
+                    "equivalences": [datasets.Value("string")],
+                    "attributes": [datasets.Value("string")],
+                    "normalizations": [datasets.Value("string")],
+                }
+            )
+
+        elif self.config.schema == "bigbio_kb":
+            features = kb_features
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=str(_LICENSE),
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager) -> List[datasets.SplitGenerator]:
+        urls = _URLS[_DATASETNAME]
+        data_dir_train = dl_manager.download_and_extract(urls["train"])
+        data_dir_test = dl_manager.download_and_extract(urls["test"])
+        data_dir_dev = dl_manager.download_and_extract(urls["dev"])
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir_train,
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": data_dir_test,
+                    "split": "test",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": data_dir_dev,
+                    "split": "dev",
+                },
+            ),
+        ]
+
+    def _standardize_arguments_roles(self, kb_example: Dict) -> Dict:
+
+        for event in kb_example["events"]:
+            for argument in event["arguments"]:
+                role = argument["role"]
+                argument["role"] = self._ROLE_MAPPING.get(role, role)
+
+        return kb_example
+
+    def _generate_examples(self, filepath, split):
+
+        filepath = Path(filepath)
+        txt_files: List[Path] = [
+            file for file in filepath.iterdir() if file.suffix == ".txt"
+        ]
+
+        if self.config.schema == "source":
+            for i, file in enumerate(txt_files):
+                brat_content = parse_brat_file(file)
+                yield i, brat_content
+
+        elif self.config.schema == "bigbio_kb":
+            for i, file in enumerate(txt_files):
+                brat_content = parse_brat_file(file)
+                kb_example = brat_parse_to_bigbio_kb(brat_content)
+                kb_example = self._standardize_arguments_roles(kb_example)
+                kb_example["id"] = kb_example["document_id"]
+                yield i, kb_example