# coding: utf8 from __future__ import unicode_literals from ...compat import json_dumps, path2str from ...util import prints def conllu2json(input_path, output_path, n_sents=10, use_morphology=False): """ Convert conllu files into JSON format for use with train cli. use_morphology parameter enables appending morphology to tags, which is useful for languages such as Spanish, where UD tags are not so rich. """ # by @dvsrepo, via #11 explosion/spacy-dev-resources docs = [] sentences = [] conll_tuples = read_conllx(input_path, use_morphology=use_morphology) for i, (raw_text, tokens) in enumerate(conll_tuples): sentence, brackets = tokens[0] sentences.append(generate_sentence(sentence)) # Real-sized documents could be extracted using the comments on the # conluu document if(len(sentences) % n_sents == 0): doc = create_doc(sentences, i) docs.append(doc) sentences = [] output_filename = input_path.parts[-1].replace(".conll", ".json") output_filename = input_path.parts[-1].replace(".conllu", ".json") output_file = output_path / output_filename with output_file.open('w', encoding='utf-8') as f: f.write(json_dumps(docs)) prints("Created %d documents" % len(docs), title="Generated output file %s" % path2str(output_file)) def read_conllx(input_path, use_morphology=False, n=0): text = input_path.open('r', encoding='utf-8').read() i = 0 for sent in text.strip().split('\n\n'): lines = sent.strip().split('\n') if lines: while lines[0].startswith('#'): lines.pop(0) tokens = [] for line in lines: parts = line.split('\t') id_, word, lemma, pos, tag, morph, head, dep, _1, _2 = parts if '-' in id_ or '.' in id_: continue try: id_ = int(id_) - 1 head = (int(head) - 1) if head != '0' else id_ dep = 'ROOT' if dep == 'root' else dep tag = pos if tag == '_' else tag tag = tag+'__'+morph if use_morphology else tag tokens.append((id_, word, tag, head, dep, 'O')) except: print(line) raise tuples = [list(t) for t in zip(*tokens)] yield (None, [[tuples, []]]) i += 1 if n >= 1 and i >= n: break def generate_sentence(sent): (id_, word, tag, head, dep, _) = sent sentence = {} tokens = [] for i, id in enumerate(id_): token = {} token["orth"] = word[i] token["tag"] = tag[i] token["head"] = head[i] - id token["dep"] = dep[i] tokens.append(token) sentence["tokens"] = tokens return sentence def create_doc(sentences,id): doc = {} paragraph = {} doc["id"] = id doc["paragraphs"] = [] paragraph["sentences"] = sentences doc["paragraphs"].append(paragraph) return doc