| | 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, 'ufsac-public-2.1/*.xml')): |
| | context = ET.iterparse(file, events=('start', 'end')) |
| | event, root = next(context) |
| | for event, element in context: |
| | if element.tag == 'paragraph': |
| | para = element |
| | if element.tag != 'sentence': |
| | continue |
| | if event == 'end' and element.tag == 'sentence': |
| | para.remove(element) |
| | sent = element |
| | words = sent.findall('word') |
| | tokens = [token.attrib['surface_form'] if 'surface_form' in token.attrib else '_' for token in words] |
| | sent_key = ''.join([token.lower() for token in tokens]) |
| | if sent_key in used_sents: |
| | continue |
| | used_sents.add(sent_key) |
| | lemmas = [token.attrib['lemma'] if 'lemma' in token.attrib else '_' for token in words] |
| | pos_tags = [token.attrib['pos'] if 'pos' in token.attrib else '_' 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_idx': index, |
| | 'sense_keys': senses |
| | } |
| | count+=1 |
| |
|
