Create medwiki.py

medwiki.py

@@ -0,0 +1,123 @@
+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+"""MedWiki is a large-scale sentence dataset collected from Wikipedia with medical entity (UMLS) annotations. This dataset is intended for pretraining"""
+
+import csv
+import json
+import os
+
+import datasets
+
+_CITATION = """\
+@inproceedings{medwiki,
+    title={Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text}, 
+    author={Maya Varma and Laurel Orr and Sen Wu and Megan Leszczynski and Xiao Ling and Christopher Ré},
+    year={2021},
+    booktitle={Findings of the Association for Computational Linguistics: EMNLP 2021}
+}
+"""
+
+_DESCRIPTION = """\
+MedWiki is a large-scale sentence dataset collected from Wikipedia with medical entity (UMLS) annotations. This dataset is intended for pretraining.
+"""
+
+_HOMEPAGE = ""
+
+_LICENSE = ""
+
+_URLs = ["https://huggingface.co/datasets/mvarma/medwiki/blob/main/medwiki_full.zip", \
+        "https://huggingface.co/datasets/mvarma/medwiki/blob/main/medwiki_hq.zip"]
+
+
+class MedWiki(datasets.GeneratorBasedBuilder):
+    """MedWiki: A Large-Scale Sentence Dataset with Medical Entity (UMLS) Annotations"""
+
+    VERSION = datasets.Version("1.1.0")
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="medwiki", 
+            version=VERSION, 
+            description="MedWiki: A Large-Scale Sentence Dataset with Medical Entity (UMLS) Annotations"),
+    ]
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="medwiki_full", version=VERSION, description="MedWiki (Full): A Large-Scale Sentence Dataset with Medical Entity (UMLS) Annotations."),
+        datasets.BuilderConfig(name="medwiki_hq", version=VERSION, description="MedWiki (HQ): A Large-Scale Sentence Dataset with Medical Entity (UMLS) Annotations. The HQ (high quality) subset of MedWiki includes a portion of the dataset with higher-quality entity annotations."),
+    ]
+
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "mentions": datasets.Sequence(datasets.Value("string")),
+                "entities": datasets.Sequence(datasets.Value("string")),
+                "entity_titles": datasets.Sequence(datasets.Value("string")),
+                "types": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
+                "spans": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))),
+                "sentence": datasets.Value("string"),
+                "sent_idx_unq": datasets.Value("int32"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,  
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        my_urls = _URLs[self.config.name]
+        data_dir = dl_manager.download_and_extract(my_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "train.jsonl"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "test.jsonl"),
+                    "split": "test"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "dev.jsonl"),
+                    "split": "dev",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split ):
+        """ Yields examples as (key, example) tuples. """
+
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+                yield id_, {
+                    "mentions": data["mentions"],
+                    "entities": data["entities"],
+                    "entity_titles": data['entity_titles'],
+                    "types": data["types"],
+                    "spans": data["spans"],
+                    "sentence": data["sentence"],
+                    "sent_idx_unq": data["sent_idx_unq"],
+                }