Upload bionlp2.py

bionlp2.py

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+""" NER dataset compiled by T-NER library https://github.com/asahi417/tner/tree/master/tner """
+import json
+from itertools import chain
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+_DESCRIPTION = """[BioNLP2004 NER dataset](https://aclanthology.org/W04-1213.pdf)"""
+_NAME = "bionlp"
+_VERSION = "1.0.0"
+_CITATION = """
+@inproceedings{collier-kim-2004-introduction,
+    title = "Introduction to the Bio-entity Recognition Task at {JNLPBA}",
+    author = "Collier, Nigel  and
+      Kim, Jin-Dong",
+    booktitle = "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications ({NLPBA}/{B}io{NLP})",
+    month = aug # " 28th and 29th",
+    year = "2004",
+    address = "Geneva, Switzerland",
+    publisher = "COLING",
+    url = "https://aclanthology.org/W04-1213",
+    pages = "73--78",
+}
+https://huggingface.co/datasets/chintagunta85/bionlp/raw/main/test_bionlp.json
+"""
+
+_HOME_PAGE = "https://huggingface.co/datasets/chintagunta85"
+# https://huggingface.co/datasets/chintagunta85/bionlp/raw/main/train_bionlp.json
+_URL = f'https://huggingface.co/datasets/chintagunta85/{_NAME}/raw/main'
+_URLS = {
+    str(datasets.Split.TEST): [f'{_URL}/test_bionlp.json'],
+    str(datasets.Split.TRAIN): [f'{_URL}/train_bionlp.json'],
+    str(datasets.Split.VALIDATION): [f'{_URL}/valid_bionlp.json'],
+}
+
+
+
+def map_ner_tags(tlist):
+    nlist=[]
+    for indx in tlist:
+        #if(inv_map[indx]):
+            # print(inv_map[indx], custom_names.index(inv_map[indx]), indx)
+        nlist.append(custom_names.index(inv_map[indx]))
+    return nlist
+
+class BioNLP2004Config(datasets.BuilderConfig):
+    """BuilderConfig"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(BioNLP2004Config, self).__init__(**kwargs)
+
+
+class BioNLP2004(datasets.GeneratorBasedBuilder):
+    """Dataset."""
+
+    BUILDER_CONFIGS = [
+        BioNLP2004Config(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
+    ]
+
+
+
+    def _split_generators(self, dl_manager):
+        downloaded_file = dl_manager.download_and_extract(_URLS)
+        return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]})
+                for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]]
+
+    def _generate_examples(self, filepaths):
+        custom_names = ['O','B-GENE','I-GENE','B-CHEMICAL','I-CHEMICAL','B-DISEASE','I-DISEASE',
+         'B-DNA', 'I-DNA', 'B-RNA', 'I-RNA', 'B-CELL_LINE', 'I-CELL_LINE', 'B-CELL_TYPE', 'I-CELL_TYPE', 
+         'B-PROTEIN', 'I-PROTEIN', 'B-SPECIES', 'I-SPECIES']
+
+        pre_def = {"O": 0, "B-DNA": 1, "I-DNA": 2, "B-PROTEIN": 3, "I-PROTEIN": 4,
+         "B-CELL_TYPE": 5, "I-CELL_TYPE": 6, "B-CELL_LINE": 7, "I-CELL_LINE": 8,
+         "B-RNA": 9, "I-RNA": 10}
+        inv_map = {0: 'O', 1: 'B-DNA', 2: 'I-DNA', 3: 'B-PROTEIN', 4: 'I-PROTEIN', 
+         5: 'B-CELL_TYPE', 6: 'I-CELL_TYPE', 7: 'B-CELL_LINE', 8: 'I-CELL_LINE', 9: 'B-RNA', 10: 'I-RNA'}    
+    
+        _key = 0
+        for filepath in filepaths:
+            logger.info(f"generating examples from = {filepath}")
+            with open(filepath, encoding="utf-8") as f:
+                _list = [i for i in f.read().split('\n') if len(i) > 0]
+                for i in _list:
+                    data = json.loads(i)
+                    #print(data)
+                    
+                    nlist = []
+                    for indx in data["ner_tags"]:
+                        nlist.append(custom_names.index(inv_map[indx]))
+                    #data['ner_tags'] = map_ner_tags(data['ner_tags'])
+                    data["ner_tags"]=nlist
+                    yield _key, data
+                    _key += 1
+
+    def _info(self):
+        custom_names = ['O','B-GENE','I-GENE','B-CHEMICAL','I-CHEMICAL','B-DISEASE','I-DISEASE',
+            'B-DNA', 'I-DNA', 'B-RNA', 'I-RNA', 'B-CELL_LINE', 'I-CELL_LINE', 'B-CELL_TYPE', 'I-CELL_TYPE', 
+            'B-PROTEIN', 'I-PROTEIN', 'B-SPECIES', 'I-SPECIES']
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "tags": datasets.Sequence(datasets.Value("int32")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=custom_names
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOME_PAGE,
+            citation=_CITATION,
+        )