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96 lines
3.2 KiB
Python
96 lines
3.2 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from ...compat import json_dumps, path2str
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from ...util import prints
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from ...gold import iob_to_biluo
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def conllubio2json(input_path, output_path, n_sents=10, use_morphology=False, lang=None):
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"""
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Convert conllu files into JSON format for use with train cli.
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use_morphology parameter enables appending morphology to tags, which is
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useful for languages such as Spanish, where UD tags are not so rich.
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"""
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# by @dvsrepo, via #11 explosion/spacy-dev-resources
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docs = []
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sentences = []
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conll_tuples = read_conllx(input_path, use_morphology=use_morphology)
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for i, (raw_text, tokens) in enumerate(conll_tuples):
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sentence, brackets = tokens[0]
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sentences.append(generate_sentence(sentence))
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# Real-sized documents could be extracted using the comments on the
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# conluu document
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if(len(sentences) % n_sents == 0):
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doc = create_doc(sentences, i)
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docs.append(doc)
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sentences = []
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output_filename = input_path.parts[-1].replace(".conll", ".json")
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output_filename = input_path.parts[-1].replace(".conllu", ".json")
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output_file = output_path / output_filename
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with output_file.open('w', encoding='utf-8') as f:
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f.write(json_dumps(docs))
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prints("Created %d documents" % len(docs),
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title="Generated output file %s" % path2str(output_file))
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def read_conllx(input_path, use_morphology=False, n=0):
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text = input_path.open('r', encoding='utf-8').read()
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i = 0
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for sent in text.strip().split('\n\n'):
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lines = sent.strip().split('\n')
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if lines:
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while lines[0].startswith('#'):
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lines.pop(0)
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tokens = []
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for line in lines:
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parts = line.split('\t')
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id_, word, lemma, pos, tag, morph, head, dep, _1, ner = parts
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if '-' in id_ or '.' in id_:
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continue
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try:
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id_ = int(id_) - 1
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head = (int(head) - 1) if head != '0' else id_
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dep = 'ROOT' if dep == 'root' else dep
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tag = pos if tag == '_' else tag
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tag = tag+'__'+morph if use_morphology else tag
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ner = ner if ner else 'O'
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tokens.append((id_, word, tag, head, dep, ner))
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except:
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print(line)
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raise
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tuples = [list(t) for t in zip(*tokens)]
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yield (None, [[tuples, []]])
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i += 1
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if n >= 1 and i >= n:
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break
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def generate_sentence(sent):
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(id_, word, tag, head, dep, ner) = sent
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sentence = {}
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tokens = []
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ner = iob_to_biluo(ner)
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for i, id in enumerate(id_):
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token = {}
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token["orth"] = word[i]
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token["tag"] = tag[i]
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token["head"] = head[i] - id
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token["dep"] = dep[i]
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token["ner"] = ner[i]
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tokens.append(token)
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sentence["tokens"] = tokens
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return sentence
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def create_doc(sentences,id):
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doc = {}
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paragraph = {}
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doc["id"] = id
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doc["paragraphs"] = []
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paragraph["sentences"] = sentences
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doc["paragraphs"].append(paragraph)
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return doc
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