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# Author: Roman Janík
# Script for creating a CoNLL format of my dataset from text files and Label Studio annotations.
#
import argparse
import json
import os
from nltk.tokenize import word_tokenize, sent_tokenize
def get_args():
parser = argparse.ArgumentParser(description="Script for creating a CoNLL format of my dataset from text files and Label Studio annotations.")
parser.add_argument("-s", "--source_file", required=True, help="Path to source Label Studio json annotations file.")
parser.add_argument("-o", "--output_dir", required=True, help="Output dir for CoNLL dataset splits.")
args = parser.parse_args()
return args
def fix_quotes(sentence):
return map(lambda word: word.replace('``', '"').replace("''", '"'), sentence)
def process_text_annotations(text, annotations):
entity_types_map = {
"Personal names": "p",
"Institutions": "i",
"Geographical names": "g",
"Time expressions": "t",
"Artifact names/Objects": "o"
}
sentences = sent_tokenize(text, language="czech")
sentences_t = [fix_quotes(word_tokenize(x, language="czech")) for x in sentences]
sentences_idx = []
start = 0
for i, c in enumerate(text):
if not c.isspace():
start = i
break
for sentence in sentences_t:
sentence_idx = []
for word in sentence:
end = start + len(word)
sentence_idx.append({"word": word, "start": start, "end": end, "entity_type": "O"})
for i, _ in enumerate(text):
if end + i < len(text) and not text[end + i].isspace():
start = end + i
break
sentences_idx.append(sentence_idx)
for n_entity in annotations:
begin = True
done = False
for sentence_idx in sentences_idx:
for word_idx in sentence_idx:
if word_idx["start"] >= n_entity["start"]\
and (word_idx["end"] <= n_entity["end"]
or (not text[word_idx["end"]-1].isalnum()) and len(word_idx["word"]) > 1) and begin:
word_idx["entity_type"] = "B-" + entity_types_map[n_entity["labels"][0]]
begin = False
if word_idx["end"] >= n_entity["end"]:
done = True
break
elif word_idx["start"] > n_entity["start"] and (word_idx["end"] <= n_entity["end"]
or (not text[word_idx["end"]-1].isalnum() and text[word_idx["start"]].isalnum())):
word_idx["entity_type"] = "I-" + entity_types_map[n_entity["labels"][0]]
if word_idx["end"] >= n_entity["end"]:
done = True
break
elif word_idx["end"] > n_entity["end"]:
done = True
break
if done:
break
conll_sentences = []
for sentence_idx in sentences_idx:
conll_sentence = map(lambda w: w["word"] + " " + w["entity_type"], sentence_idx)
conll_sentences.append("\n".join(conll_sentence))
conll_sentences = "\n\n".join(conll_sentences)
return conll_sentences
def main():
args = get_args()
print("Script for creating a CoNLL format of my dataset from text files and Label Studio annotations."
"Script goes through page text files and their annotations json record. "
"Output CoNLL dataset file is saved to output directory.")
with open(args.source_file, encoding="utf-8") as f:
annotations = json.load(f)
print("Starting documents processing...")
with open(os.path.join(args.output_dir, "poner.conll"), "w", encoding="utf-8") as f:
for page in annotations:
page_text_path = page["text"].replace("http://localhost:8081", "../../../datasets/poner1.0/data")
with open(page_text_path, encoding="utf-8") as p_f:
page_text = p_f.read()
processed_page = process_text_annotations(page_text, page["ner"])
f.write(processed_page + "\n\n")
print("Annotations are processed.")
if __name__ == '__main__':
main()
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