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ufsac-public-2.1.tar.xz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:39c05f5ac3c657d1892ecb94d2207a02026406bc3e44dc50621e50fec7eed6e9
+size 196134720

ufsac_dataset.py

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+import datasets
+import xml.etree.cElementTree as ET
+from glob import glob
+import os
+
+_UFSAC_FILE = 'ufsac-public-2.1.tar.xz'
+
+class UFSAC(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIG_CLASS = datasets.BuilderConfig
+
+    def _info(self):
+        feature = {
+            'tokens': datasets.Sequence(datasets.Value('string')),
+            'lemmas': datasets.Sequence(datasets.Value('string')),
+            'pos_tags': datasets.Sequence(datasets.Value('string')),
+            'target_idx': datasets.Value('int32'),
+            'sense_keys': datasets.Sequence(datasets.Value('string')),
+        }
+
+        return datasets.DatasetInfo(
+            features=datasets.Features(feature),
+            description = 'UFSAC: the unified Sense Annotated Corpora and Tool'
+        )
+    
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(_UFSAC_FILE)
+        return datasets.SplitGenerator(name = datasets.Split().TRAIN, gen_kwargs={'data_dir': data_dir})
+    
+    def _generate_examples(self, data_dir):
+        used_sents = set()
+        count = 0
+        for file in glob(os.path.join(data_dir, '*.xml')):
+            tree = ET.parse(file)
+            root = tree.getroot()
+            for sent in root.iter('sentence'):
+                words = sent.findall('word')
+                tokens = [token.attrib['surface_form'] for token in words]
+                sent_key = ''.join(tokens)
+                if sent_key not in used_sents:
+                    used_sents.add(sent_key)
+                else:
+                    continue
+                lemmas = [token.attrib['lemma'] for token in words]
+                pos_tags = [token.attrib['pos'] for token in words]
+                for index, word in enumerate(words):
+                    if 'wn30_key' in word.attrib:
+                        senses = word.attrib['wn30_key'].split(';')
+                        yield count, {
+                            'tokens': tokens,
+                            'lemmas': lemmas,
+                            'pos_tags': pos_tags,
+                            'target_index': index,
+                            'sense_keys': senses
+                        }