nlp/spacy_nlp
2019-03-06 12:19:43 +01:00

60 lines
1.9 KiB
Python
Executable File

#!/usr/bin/env python3
# coding=utf-8
import argparse
import os
import spacy
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
with open(args.input) as input_file:
text = input_file.read()
# Run spacy nlp over the text
doc = nlp(text)
# 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 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()