mirror of
https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nlp.git
synced 2024-12-26 22:34:18 +00:00
63 lines
2.2 KiB
Python
Executable File
63 lines
2.2 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
# coding=utf-8
|
|
|
|
|
|
import argparse
|
|
import os
|
|
import spacy
|
|
import textwrap
|
|
|
|
|
|
parser = argparse.ArgumentParser(description="Tag a .txt file with spaCy and \
|
|
save it in .vrt format")
|
|
parser.add_argument("-i",
|
|
dest="input",
|
|
help="Input file.",
|
|
required=True)
|
|
parser.add_argument("-l",
|
|
choices=["de", "en", "es", "fr", "pt"],
|
|
dest="lang",
|
|
help="Language for tagging",
|
|
required=True)
|
|
parser.add_argument("-o",
|
|
dest="output",
|
|
help="Output file.",
|
|
required=True)
|
|
args = parser.parse_args()
|
|
|
|
|
|
SPACY_MODELS = {"de": "de_core_news_sm", "en": "en_core_web_sm",
|
|
"es": "es_core_news_sm", "fr": "fr_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.input) 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.output, "w+")
|
|
output_file.write('<?xml version="1.0" encoding="UTF-8"?>\n<corpus>\n<text id="' + args.input.rsplit(".", 1)[0] + '">\n')
|
|
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()
|