mirror of
https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nlp.git
synced 2025-10-31 20:03:13 +00:00
72 lines
2.0 KiB
Python
Executable File
72 lines
2.0 KiB
Python
Executable File
#!/usr/bin/env python3.5
|
|
# coding=utf-8
|
|
|
|
import argparse
|
|
import os
|
|
import spacy
|
|
import textwrap
|
|
|
|
parser = argparse.ArgumentParser(
|
|
description='Tag a text file with spaCy and save it as a verticalized text file.'
|
|
)
|
|
parser.add_argument(
|
|
'i',
|
|
metavar='txt-sourcefile',
|
|
)
|
|
parser.add_argument(
|
|
'-l',
|
|
choices=['de', 'el', 'en', 'es', 'fr', 'it', 'nl', 'pt'],
|
|
dest='lang',
|
|
required=True
|
|
)
|
|
parser.add_argument(
|
|
'o',
|
|
metavar='vrt-destfile',
|
|
)
|
|
args = parser.parse_args()
|
|
|
|
SPACY_MODELS = {
|
|
'de': 'de_core_news_sm', 'el': 'el_core_news_sm', 'en': 'en_core_web_sm',
|
|
'es': 'es_core_news_sm', 'fr': 'fr_core_news_sm', 'it': 'it_core_news_sm',
|
|
'nl': 'nl_core_news_sm', 'pt': 'pt_core_news_sm'
|
|
}
|
|
|
|
# Set the language model for spacy
|
|
nlp = spacy.load(SPACY_MODELS[args.lang])
|
|
|
|
# Read text from the input file and if neccessary split it into parts with a
|
|
# length of less than 1 million characters.
|
|
with open(args.i) as input_file:
|
|
text = input_file.read()
|
|
texts = textwrap.wrap(text, 1000000, break_long_words=False)
|
|
text = None
|
|
|
|
# Create and open the output file
|
|
output_file = open(args.o, 'w+')
|
|
|
|
output_file.write(
|
|
'<?xml version="1.0" encoding="UTF-8"?>\n<corpus>\n<text id="%s">\n' % (
|
|
os.path.basename(args.i).rsplit(".", 1)[0]
|
|
)
|
|
)
|
|
for text in texts:
|
|
# Run spacy nlp over the text (partial string if above 1 million chars)
|
|
doc = nlp(text)
|
|
for sent in doc.sents:
|
|
output_file.write('<s>\n')
|
|
for token in sent:
|
|
# Skip whitespace tokens like "\n" or "\t"
|
|
if token.text.isspace():
|
|
continue
|
|
# Write all information in .vrt style to the output file
|
|
# text, lemma, simple_pos, pos, ner
|
|
output_file.write(
|
|
token.text + '\t' + token.lemma_ + '\t'
|
|
+ token.pos_ + '\t' + token.tag_ + '\t'
|
|
+ (token.ent_type_ if token.ent_type_ != '' else 'NULL') + '\n'
|
|
)
|
|
output_file.write('</s>\n')
|
|
output_file.write('</text>\n</corpus>')
|
|
|
|
output_file.close()
|