Add prototype

vre_nlp_node/spacy_nlp

@@ -0,0 +1,59 @@
+#!/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="' + os.path.basename(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()