Updated code to include other hand correction.

master
Luka 2 years ago
parent 2e36fd0eaa
commit 7c4b40eb7c

@ -230,11 +230,17 @@ def build_links(all_edges):
for sentence_edges in paragraph_edges:
s = etree.Element('linkGrp')
random_id = ''
sentence_id = ''
for token_edges in sentence_edges:
if not random_id:
random_id = token_edges['source_ids'][0] if len(token_edges['source_ids']) > 0 else token_edges['target_ids'][0]
sentence_id = '.'.join(random_id.split('.')[:3])
if not sentence_id:
if len(token_edges['source_ids']) > 0:
random_source_id = token_edges['source_ids'][0]
sentence_id += '.'.join(random_source_id.split('.')[:3])
elif len(token_edges['target_ids']) > 0:
random_target_id = token_edges['target_ids'][0]
if len(token_edges['source_ids']) > 0:
sentence_id += ' #'
sentence_id += '.'.join(random_target_id.split('.')[:3])
link = etree.Element('link')
labels = '|'.join(token_edges['labels']) if len(token_edges['labels']) > 0 else 'ID'
link.set('type', labels)

@ -9,6 +9,7 @@ from conllu import TokenList
import conllu
import classla
import copy
from classla.pipeline.tokenize_processor import TokenizeProcessor
from lxml import etree
@ -18,6 +19,107 @@ from src.create_tei import construct_sentence_from_list, \
logging.basicConfig(level=logging.INFO)
def add_source(svala_i, source_i, sentence_string_id_split, source, el):
source_id = "s" + svala_i
source_token_id = f'{sentence_string_id_split[0]}s.{".".join(sentence_string_id_split[1:])}.{source_i}'
token_tag = 'w' if el.tag.startswith('w') else 'pc'
source.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'id': source_token_id,
'space_after': False, 'svala_id': source_id})
def add_target(svala_i, target_i, sentence_string_id_split, target, el):
target_id = "t" + svala_i
target_token_id = f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}.{target_i}'
token_tag = 'w' if el.tag.startswith('w') else 'pc'
target.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'id': target_token_id,
'space_after': False, 'svala_id': target_id})
def add_edges(source_id, target_id, svala_data, edges, source_token_id, target_token_id):
edge_id = "e-" + source_id + "-" + target_id
labels = svala_data['edges'][edge_id]['labels']
edges.append({'source_ids': [source_token_id], 'target_ids': [target_token_id], 'labels': labels})
def create_edges(svala_data, source_par, target_par):
source_mapper = {el['svala_id']: el['id'] for source in source_par for el in source}
target_mapper = {el['svala_id']: el['id'] for target in target_par for el in target}
source_ids = [el['svala_id'] for source in source_par for el in source]
target_ids = [el['svala_id'] for target in target_par for el in target]
source_sentence_ids = [set([el['svala_id'] for el in source]) for source in source_par]
target_sentence_ids = [set([el['svala_id'] for el in target]) for target in target_par]
# create links to ids mapper
links_ids_mapper = {}
for k, v in svala_data['edges'].items():
for el in v['ids']:
if el not in links_ids_mapper:
links_ids_mapper[el] = []
links_ids_mapper[el].append(k)
# create edge order
edges_order = []
edges_processed = set()
s_i = 0
t_i = 0
check_s_i = True
while s_i < len(source_ids) or t_i < len(target_ids):
# take care of getting ids over desired s_i/t_i
if check_s_i and s_i >= len(source_ids):
check_s_i = False
if not check_s_i and t_i >= len(target_ids):
check_s_i = True
if check_s_i:
id_of_interest = source_ids[s_i]
s_i += 1
check_s_i = not check_s_i
else:
id_of_interest = target_ids[t_i]
t_i += 1
check_s_i = not check_s_i
any_addition = False
# if id_of_interest not in links_ids_mapper:
# print('NOOOOO')
for edge_id in links_ids_mapper[id_of_interest]:
if edge_id not in edges_processed:
any_addition = True
edges_order.append(edge_id)
edges_processed.add(edge_id)
if not any_addition:
check_s_i = not check_s_i
sentence_edges = []
source_sent_id = 0
target_sent_id = 0
# actually add edges
edges = []
for edge_id in edges_order:
labels = svala_data['edges'][edge_id]['labels']
source_ids = [source_mapper[el] for el in svala_data['edges'][edge_id]['ids'] if el in source_mapper]
target_ids = [target_mapper[el] for el in svala_data['edges'][edge_id]['ids'] if el in target_mapper]
ids = svala_data['edges'][edge_id]['ids']
source_ok = [el[0] == 't' or el in source_sentence_ids[source_sent_id] for el in ids]
source_ok_all = all(source_ok)
if not source_ok_all:
source_sent_id += 1
target_ok = [el[0] == 's' or el in target_sentence_ids[target_sent_id] for el in ids]
target_ok_all = all(target_ok)
if not target_ok_all:
target_sent_id += 1
if not source_ok_all or not target_ok_all:
sentence_edges.append(edges)
edges = []
edges.append({'source_ids': source_ids, 'target_ids': target_ids, 'labels': labels})
return sentence_edges
def add_token(svala_i, source_i, target_i, el, source, target, edges, svala_data, sentence_string_id):
source_id = "s" + svala_i
target_id = "t" + svala_i
@ -25,7 +127,7 @@ def add_token(svala_i, source_i, target_i, el, source, target, edges, svala_data
labels = svala_data['edges'][edge_id]['labels']
sentence_string_id_split = sentence_string_id.split('.')
source_token_id = f'{sentence_string_id_split[0]}s.{".".join(sentence_string_id_split[1:])}.{source_i}'
target_token_id = f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}.{source_i}'
target_token_id = f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}.{target_i}'
token_tag = 'w' if el.tag.startswith('w') else 'pc'
lemma = el.attrib['lemma'] if token_tag == 'w' else el.text
source.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'lemma': lemma, 'id': source_token_id, 'space_after': False})
@ -44,7 +146,139 @@ def add_error_token(el, out_list, sentence_string_id, out_list_i, out_list_ids,
out_list_ids.append(source_token_id)
def add_errors(svala_i, source_i, target_i, error, source, target, edges, svala_data, sentence_string_id):
def add_error_token_source_target_only(el, out_list, sentence_string_id, out_list_i, is_source, s_t_id):
sentence_string_id_split = sentence_string_id.split('.')
source_token_id = f'{sentence_string_id_split[0]}s.{".".join(sentence_string_id_split[1:])}.{out_list_i}' if is_source \
else f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}.{out_list_i}'
token_tag = 'w' if el.tag.startswith('w') else 'pc'
out_list.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'id': source_token_id, 'space_after': False, 'svala_id': s_t_id})
def add_errors1_0_1(svala_i, source_i, target_i, error, source, target, svala_data, sentence_string_id, edges=None):
source_edge_ids = []
target_edge_ids = []
source_ids = []
target_ids = []
# solar5.7
for el in error:
if el.tag.startswith('w') or el.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
source_edge_ids.append(source_id)
add_error_token(el, source, sentence_string_id, source_i, source_ids, True)
source_i += 1
svala_i += 1
elif el.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
elif el.tag.startswith('p'):
for p_el in el:
if p_el.tag.startswith('w') or p_el.tag.startswith('pc'):
ind = str(svala_i)
target_id = "t" + ind
target_edge_ids.append(target_id)
add_error_token(p_el, target, sentence_string_id, target_i, target_ids, False)
target_i += 1
svala_i += 1
elif p_el.tag.startswith('c') and len(target) > 0:
target[-1]['space_after'] = True
elif el.tag.startswith('u2'):
for el_l2 in el:
if el_l2.tag.startswith('w') or el_l2.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
source_edge_ids.append(source_id)
add_error_token(el_l2, source, sentence_string_id, source_i, source_ids, True)
source_i += 1
svala_i += 1
elif el_l2.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
elif el_l2.tag.startswith('u3'):
for el_l3 in el_l2:
if el_l3.tag.startswith('w') or el_l3.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
source_edge_ids.append(source_id)
add_error_token(el_l3, source, sentence_string_id, source_i, source_ids, True)
source_i += 1
svala_i += 1
elif el_l3.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
elif el_l3.tag.startswith('u4'):
for el_l4 in el_l3:
if el_l4.tag.startswith('w') or el_l4.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
source_edge_ids.append(source_id)
add_error_token(el_l4, source, sentence_string_id, source_i, source_ids, True)
source_i += 1
svala_i += 1
elif el_l4.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
elif el_l4.tag.startswith('u5'):
for el_l5 in el_l4:
if el_l5.tag.startswith('w') or el_l5.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
source_edge_ids.append(source_id)
add_error_token(el_l5, source, sentence_string_id, source_i, source_ids, True)
source_i += 1
svala_i += 1
elif el_l5.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
# TODO NOT SURE IF THIS SHOULD BE COMMENTED! IF IT IS NOT THERE ARE ERRORS ON 2ND lvl of errors, where some words are duplicated
for p_el in el:
if p_el.tag.startswith('w') or p_el.tag.startswith('pc'):
ind = str(svala_i)
target_id = "t" + ind
target_edge_ids.append(target_id)
add_error_token(p_el, target, sentence_string_id, target_i, target_ids, False)
target_i += 1
svala_i += 1
elif p_el.tag.startswith('c') and len(target) > 0:
target[-1]['space_after'] = True
if edges is not None:
edge_ids = sorted(source_edge_ids) + sorted(target_edge_ids)
edge_id = "e-" + "-".join(edge_ids)
edges.append({'source_ids': source_ids, 'target_ids': target_ids, 'labels': svala_data['edges'][edge_id]['labels']})
return svala_i, source_i, target_i
def add_errors(svala_i, source_i, target_i, error, source, target, svala_data, sentence_string_id, edges=None):
source_edge_ids = []
target_edge_ids = []
source_ids = []
@ -159,9 +393,120 @@ def add_errors(svala_i, source_i, target_i, error, source, target, edges, svala_
# elif p_el.tag.startswith('c') and len(target) > 0:
# target[-1]['space_after'] = True
edge_ids = sorted(source_edge_ids) + sorted(target_edge_ids)
edge_id = "e-" + "-".join(edge_ids)
edges.append({'source_ids': source_ids, 'target_ids': target_ids, 'labels': svala_data['edges'][edge_id]['labels']})
if edges is not None:
edge_ids = sorted(source_edge_ids) + sorted(target_edge_ids)
edge_id = "e-" + "-".join(edge_ids)
edges.append({'source_ids': source_ids, 'target_ids': target_ids, 'labels': svala_data['edges'][edge_id]['labels']})
return svala_i, source_i, target_i
def add_errors_source_target_only(svala_i, source_i, target_i, error, source, target, svala_data, sentence_string_id):
# solar5.7
for el in error:
if el.tag.startswith('w') or el.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
add_error_token_source_target_only(el, source, sentence_string_id, source_i, True, source_id)
source_i += 1
svala_i += 1
elif el.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
elif el.tag.startswith('p'):
for p_el in el:
if p_el.tag.startswith('w') or p_el.tag.startswith('pc'):
ind = str(svala_i)
target_id = "t" + ind
add_error_token_source_target_only(p_el, target, sentence_string_id, target_i, False, target_id)
target_i += 1
svala_i += 1
elif p_el.tag.startswith('c') and len(target) > 0:
target[-1]['space_after'] = True
elif el.tag.startswith('u2'):
for el_l2 in el:
if el_l2.tag.startswith('w') or el_l2.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
add_error_token_source_target_only(el_l2, source, sentence_string_id, source_i, True, source_id)
source_i += 1
svala_i += 1
elif el_l2.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
elif el_l2.tag.startswith('u3'):
for el_l3 in el_l2:
if el_l3.tag.startswith('w') or el_l3.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
add_error_token_source_target_only(el_l3, source, sentence_string_id, source_i, True, source_id)
source_i += 1
svala_i += 1
elif el_l3.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
elif el_l3.tag.startswith('u4'):
for el_l4 in el_l3:
if el_l4.tag.startswith('w') or el_l4.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
add_error_token_source_target_only(el_l4, source, sentence_string_id, source_i, True, source_id)
source_i += 1
svala_i += 1
elif el_l4.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
elif el_l4.tag.startswith('u5'):
for el_l5 in el_l4:
if el_l5.tag.startswith('w') or el_l5.tag.startswith('pc'):
ind = str(svala_i)
source_id = "s" + ind
add_error_token_source_target_only(el_l5, source, sentence_string_id, source_i, True, source_id)
source_i += 1
svala_i += 1
elif el_l5.tag.startswith('c') and len(source) > 0:
source[-1]['space_after'] = True
# TODO NOT SURE IF THIS SHOULD BE COMMENTED! IF IT IS NOT THERE ARE ERRORS ON 2ND lvl of errors, where some words are duplicated
for p_el in el:
if p_el.tag.startswith('w') or p_el.tag.startswith('pc'):
ind = str(svala_i)
target_id = "t" + ind
add_error_token_source_target_only(p_el, target, sentence_string_id, target_i, False, target_id)
target_i += 1
svala_i += 1
elif p_el.tag.startswith('c') and len(target) > 0:
target[-1]['space_after'] = True
# edge_ids = sorted(source_edge_ids) + sorted(target_edge_ids)
# edge_id = "e-" + "-".join(edge_ids)
# edges.append({'source_ids': source_ids, 'target_ids': target_ids, 'labels': svala_data['edges'][edge_id]['labels']})
return svala_i, source_i, target_i
@ -185,7 +530,199 @@ def create_conllu(interest_list, sentence_string_id):
return conllu_result.serialize()
def process_file(et, args, nlp):
def process_solar2_paragraph(sentences, paragraph, svala_i, svala_data, add_errors_func, nlp, complete_source_conllu, complete_target_conllu):
etree_source_sentences = []
etree_target_sentences = []
sentence_edges = []
for sentence_id, sentence in enumerate(sentences):
source = []
target = []
edges = []
sentence_id += 1
source_i = 1
target_i = 1
sentence_string_id = paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'] + f'.{sentence_id}'
for el in sentence:
if el.tag.startswith('w'):
add_token(str(svala_i), source_i, target_i, el, source, target, edges, svala_data, sentence_string_id)
svala_i += 1
source_i += 1
target_i += 1
elif el.tag.startswith('pc'):
add_token(str(svala_i), source_i, target_i, el, source, target, edges, svala_data, sentence_string_id)
svala_i += 1
source_i += 1
target_i += 1
elif el.tag.startswith('u'):
svala_i, source_i, target_i = add_errors_func(svala_i, source_i, target_i, el, source, target,
svala_data, sentence_string_id, edges=edges)
elif el.tag.startswith('c'):
if len(source) > 0:
source[-1]['space_after'] = True
if len(target) > 0:
target[-1]['space_after'] = True
sentence_edges.append(edges)
if len(source) > 0:
source_conllu = create_conllu(source, sentence_string_id)
if len(target) > 0:
target_conllu = create_conllu(target, sentence_string_id)
if len(source) > 0:
source_conllu_annotated = nlp(source_conllu).to_conll()
if len(target) > 0:
target_conllu_annotated = nlp(target_conllu).to_conll()
if len(source) > 0:
complete_source_conllu += source_conllu_annotated
complete_target_conllu += target_conllu_annotated
if len(source) > 0:
source_conllu_parsed = conllu.parse(source_conllu_annotated)[0]
if len(target) > 0:
target_conllu_parsed = conllu.parse(target_conllu_annotated)[0]
if len(source) > 0:
etree_source_sentences.append(construct_sentence_from_list(str(sentence_id), source_conllu_parsed, True))
if len(target) > 0:
etree_target_sentences.append(construct_sentence_from_list(str(sentence_id), target_conllu_parsed, False))
return etree_source_sentences, etree_target_sentences, sentence_edges
def read_raw_text(path):
with open(path, 'r') as rf:
return rf.read()
def map_svala_tokenized(svala_data_part, tokenized_paragraph):
paragraph_res = []
svala_data_i = 0
for sentence in tokenized_paragraph:
sentence_res = []
for tok in sentence:
tag = 'pc' if 'xpos' in tok and tok['xpos'] == 'Z' else 'w'
if 'misc' in tok:
assert tok['misc'] == 'SpaceAfter=No'
space_after = not 'misc' in tok
if svala_data_part[svala_data_i]['text'].strip() != tok['text']:
raise 'Word mismatch!'
sentence_res.append({'token': tok['text'], 'tag': tag, 'id': tok['id'][0], 'space_after': space_after, 'svala_id': svala_data_part[svala_data_i]['id']})
svala_data_i += 1
paragraph_res.append(sentence_res)
return paragraph_res
def update_ids(pretag, in_list):
for el in in_list:
el['id'] = f'{pretag}.{el["id"]}'
def process_obeliks_paragraph(sentences, paragraph, svala_i, svala_data, add_errors_func, nlp, complete_source_conllu, complete_target_conllu, source_raw_text, target_raw_text, nlp_tokenize):
etree_source_sentences = []
etree_target_sentences = []
sentence_edges = []
if source_raw_text is not None:
text = read_raw_text(source_raw_text)
raw_text, source_tokenized, metadocument = nlp_tokenize.processors['tokenize']._tokenizer.tokenize(text)
# source_tokenized = nlp_tokenize()
source_res = map_svala_tokenized(svala_data['source'], source_tokenized)
if target_raw_text is not None:
text = read_raw_text(target_raw_text)
raw_text, target_tokenized, metadocument = nlp_tokenize.processors['tokenize']._tokenizer.tokenize(text)
target_res = map_svala_tokenized(svala_data['target'], target_tokenized)
# TODO RETURN IF SOURCE AND TARGET ARE NOT NONE
par_source = []
par_target = []
for sentence_id, sentence in enumerate(sentences):
source = []
target = []
sentence_id += 1
source_i = 1
target_i = 1
sentence_string_id = paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'] + f'.{sentence_id}'
if sentence_string_id == 'solar185.2.1':
print('HERE!')
sentence_string_id_split = sentence_string_id.split('.')
for el in sentence:
if el.tag.startswith('w'):
if source_raw_text is None:
add_source(str(svala_i), source_i, sentence_string_id_split, source, el)
if target_raw_text is None:
add_target(str(svala_i), target_i, sentence_string_id_split, target, el)
# add_edges(source_id, target_id, svala_data, edges, source_token_id, target_token_id)
svala_i += 1
source_i += 1
target_i += 1
elif el.tag.startswith('pc'):
if source_raw_text is None:
add_source(str(svala_i), source_i, sentence_string_id_split, source, el)
if target_raw_text is None:
add_target(str(svala_i), target_i, sentence_string_id_split, target, el)
# add_edges(source_id, target_id, svala_data, edges, source_token_id, target_token_id)
svala_i += 1
source_i += 1
target_i += 1
elif el.tag.startswith('u'):
if source_raw_text is None or target_raw_text is None:
svala_i, source_i, target_i = add_errors_source_target_only(svala_i, source_i, target_i, el, source, target, svala_data, sentence_string_id)
else:
svala_i, source_i, target_i = add_errors_func(svala_i, source_i, target_i, el, source, target,
svala_data, sentence_string_id)
elif el.tag.startswith('c'):
if len(source) > 0:
source[-1]['space_after'] = True
if len(target) > 0:
target[-1]['space_after'] = True
if source_raw_text is not None and sentence_id - 1 < len(source_res):
source = source_res[sentence_id - 1]
update_ids(f'{sentence_string_id_split[0]}s.{".".join(sentence_string_id_split[1:])}', source)
if len(source) > 0:
source_conllu = create_conllu(source, sentence_string_id)
if target_raw_text is not None and sentence_id - 1 < len(target_res):
target = target_res[sentence_id - 1]
update_ids(f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}', target)
par_source.append(source)
par_target.append(target)
if len(target) > 0:
target_conllu = create_conllu(target, sentence_string_id)
if len(source) > 0:
source_conllu_annotated = nlp(source_conllu).to_conll()
if len(target) > 0:
target_conllu_annotated = nlp(target_conllu).to_conll()
if len(source) > 0:
complete_source_conllu += source_conllu_annotated
if len(target) > 0:
complete_target_conllu += target_conllu_annotated
if len(source) > 0:
source_conllu_parsed = conllu.parse(source_conllu_annotated)[0]
if len(target) > 0:
target_conllu_parsed = conllu.parse(target_conllu_annotated)[0]
if len(source) > 0:
etree_source_sentences.append(construct_sentence_from_list(str(sentence_id), source_conllu_parsed, True))
if len(target) > 0:
etree_target_sentences.append(construct_sentence_from_list(str(sentence_id), target_conllu_parsed, False))
sentence_edges = create_edges(svala_data, par_source, par_target)
return etree_source_sentences, etree_target_sentences, sentence_edges
def process_file(et, args, nlp, nlp_tokenize):
if os.path.exists(args.results_folder):
shutil.rmtree(args.results_folder)
os.mkdir(args.results_folder)
@ -204,6 +741,8 @@ def process_file(et, args, nlp):
file_name = file_name.replace('/', '_')
svala_path = os.path.join(args.svala_folder, file_name)
corrected_svala_path = os.path.join(args.corrected_svala_folder, file_name)
raw_texts_path = os.path.join(args.svala_generated_text_folder, file_name)
# skip files that are not svala annotated (to enable short examples)
if not os.path.isdir(svala_path):
continue
@ -222,67 +761,27 @@ def process_file(et, args, nlp):
# read json
svala_file = os.path.join(svala_path, svala_dict[paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id']])
jf = open(svala_file)
corrected_svala_file = os.path.join(corrected_svala_path, svala_dict[paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id']])
if os.path.exists(corrected_svala_file):
print('aaa')
add_errors_func = add_errors if not os.path.exists(corrected_svala_file) else add_errors1_0_1
jf = open(svala_file) if not os.path.exists(corrected_svala_file) else open(corrected_svala_file)
svala_data = json.load(jf)
jf.close()
etree_source_sentences = []
etree_target_sentences = []
sentence_edges = []
for sentence_id, sentence in enumerate(sentences):
source = []
target = []
edges = []
sentence_id += 1
source_i = 1
target_i = 1
sentence_string_id = paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'] + f'.{sentence_id}'
for el in sentence:
if el.tag.startswith('w'):
add_token(str(svala_i), source_i, target_i, el, source, target, edges, svala_data, sentence_string_id)
svala_i += 1
source_i += 1
target_i += 1
elif el.tag.startswith('pc'):
add_token(str(svala_i), source_i, target_i, el, source, target, edges, svala_data, sentence_string_id)
svala_i += 1
source_i += 1
target_i += 1
elif el.tag.startswith('u'):
svala_i, source_i, target_i = add_errors(svala_i, source_i, target_i, el, source, target, edges, svala_data, sentence_string_id)
elif el.tag.startswith('c'):
if len(source) > 0:
source[-1]['space_after'] = True
if len(target) > 0:
target[-1]['space_after'] = True
sentence_edges.append(edges)
if len(source) > 0:
source_conllu = create_conllu(source, sentence_string_id)
if len(target) > 0:
target_conllu = create_conllu(target, sentence_string_id)
if len(source) > 0:
source_conllu_annotated = nlp(source_conllu).to_conll()
if len(target) > 0:
target_conllu_annotated = nlp(target_conllu).to_conll()
source_filename = svala_dict[paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id']][:-5] + '_source.json'
target_filename = svala_dict[paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id']][:-5] + '_target.json'
if len(source) > 0:
complete_source_conllu += source_conllu_annotated
complete_target_conllu += target_conllu_annotated
source_raw_text = os.path.join(raw_texts_path, source_filename) if os.path.exists(os.path.join(raw_texts_path, source_filename)) else None
target_raw_text = os.path.join(raw_texts_path, target_filename) if os.path.exists(os.path.join(raw_texts_path, target_filename)) else None
if len(source) > 0:
source_conllu_parsed = conllu.parse(source_conllu_annotated)[0]
if len(target) > 0:
target_conllu_parsed = conllu.parse(target_conllu_annotated)[0]
if not (source_raw_text or target_raw_text):
etree_source_sentences, etree_target_sentences, sentence_edges = process_solar2_paragraph(sentences, paragraph, svala_i, svala_data, add_errors_func, nlp,
complete_source_conllu, complete_target_conllu)
if len(source) > 0:
etree_source_sentences.append(construct_sentence_from_list(str(sentence_id), source_conllu_parsed, True))
if len(target) > 0:
etree_target_sentences.append(construct_sentence_from_list(str(sentence_id), target_conllu_parsed, False))
else:
etree_source_sentences, etree_target_sentences, sentence_edges = process_obeliks_paragraph(sentences, paragraph, svala_i,
svala_data, add_errors_func, nlp, complete_source_conllu, complete_target_conllu, source_raw_text, target_raw_text, nlp_tokenize)
etree_source_paragraphs.append(construct_paragraph_from_list(paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'].split('.')[0], paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'].split('.')[1], etree_source_sentences, True))
etree_target_paragraphs.append(construct_paragraph_from_list(paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'].split('.')[0], paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'].split('.')[1], etree_target_sentences, False))
@ -330,8 +829,9 @@ def main(args):
with open(args.solar_file, 'r') as fp:
logging.info(args.solar_file)
nlp = classla.Pipeline('sl', pos_use_lexicon=True, pos_lemma_pretag=False, tokenize_pretokenized="conllu", type='standard_jos')
nlp_tokenize = classla.Pipeline('sl', processors='tokenize', pos_lemma_pretag=True)
et = ElementTree.XML(fp.read())
process_file(et, args, nlp)
process_file(et, args, nlp, nlp_tokenize)
if __name__ == '__main__':
@ -339,10 +839,14 @@ if __name__ == '__main__':
description='Read already processed xmls, erase entries without examples and limit gigafida examples to 1 per entry.')
parser.add_argument('--solar_file', default='data/Solar2.0/solar2.xml',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--svala_folder', default='data/solar.svala.error.small',
parser.add_argument('--svala_folder', default='data/solar.svala',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--corrected_svala_folder', default='data/solar.svala.fixed.1.0.1',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--results_folder', default='data/results/solar3.0',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--svala_generated_text_folder', default='data/svala_generated_text.formatted',
help='input file in (gz or xml currently). If none, then just database is loaded')
args = parser.parse_args()
start = time.time()

@ -0,0 +1,77 @@
import argparse
import json
import logging
import os
import shutil
import time
def read_json(file):
jf = open(file)
svala_data = json.load(jf)
jf.close()
return svala_data
def compare_files(corrected_file, original_file):
# count_differences(corrected_file['source'], original_file['source'])
target = False
source = False
source_modifications = 0
for corrected_source, original_source in zip(corrected_file['source'], original_file['source']):
if corrected_source != original_source:
source_modifications += 1
target_modifications = 0
for corrected_target, original_target in zip(corrected_file['target'], original_file['target']):
if corrected_target != original_target:
target_modifications += 1
if target_modifications > 0:
target = True
if source_modifications > 0:
source = True
return target, source
def main(args):
# create mapper to corrected files
# corrected_files_mapper = {}
# for foldername in os.listdir(args.original_folder):
# orig_name = 'KUS' + foldername.split('KUS')[1]
# corrected_files_mapper[orig_name] = foldername
if os.path.exists(args.copied_folder):
shutil.rmtree(args.copied_folder)
os.makedirs(args.copied_folder)
for foldername in os.listdir(args.original_folder):
os.makedirs(os.path.join(args.copied_folder, foldername))
for filename in os.listdir(os.path.join(args.original_folder, foldername)):
of = os.path.join(args.original_folder, foldername, filename)
copy_filename_split = filename.split('_')
assert len(copy_filename_split) == 3 or len(copy_filename_split) == 2
if len(copy_filename_split) == 3:
copy_filename = copy_filename_split[0] + '_' + copy_filename_split[2]
elif len(copy_filename_split) == 2:
copy_filename = copy_filename_split[0] + '_' + copy_filename_split[1]
else:
raise 'Impossible!'
cf = os.path.join(args.copied_folder, foldername, copy_filename)
shutil.copyfile(of, cf)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Read already processed xmls, erase entries without examples and limit gigafida examples to 1 per entry.')
parser.add_argument('--copied_folder', default='data/svala_generated_text.formatted',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--original_folder', default='data/svala_generated_text.handchecks',
help='input file in (gz or xml currently). If none, then just database is loaded')
args = parser.parse_args()
start = time.time()
main(args)
logging.info("TIME: {}".format(time.time() - start))

@ -0,0 +1,81 @@
import argparse
import json
import logging
import os
import shutil
import time
def read_json(file):
jf = open(file)
svala_data = json.load(jf)
jf.close()
return svala_data
def compare_files(corrected_file, original_file):
# count_differences(corrected_file['source'], original_file['source'])
target = False
source = False
source_modifications = 0
for corrected_source, original_source in zip(corrected_file['source'], original_file['source']):
if corrected_source != original_source:
source_modifications += 1
target_modifications = 0
for corrected_target, original_target in zip(corrected_file['target'], original_file['target']):
if corrected_target != original_target:
target_modifications += 1
if target_modifications > 0:
target = True
if source_modifications > 0:
source = True
return target, source
def main(args):
# create mapper to corrected files
corrected_files_mapper = {}
for foldername in os.listdir(args.corrected_folder):
orig_name = 'KUS' + foldername.split('KUS')[1]
corrected_files_mapper[orig_name] = foldername
for foldername in os.listdir(args.original_folder):
for filename in os.listdir(os.path.join(args.original_folder, foldername)):
of = os.path.join(args.original_folder, foldername, filename)
copy_filename = filename
if filename.endswith('_problem.json'):
copy_filename = filename[:-13] + '.json'
if filename.endswith('_popravljeno.json'):
copy_filename = filename[:-13] + '.json'
cpf = os.path.join(args.copied_folder, foldername, copy_filename)
cpfol = os.path.join(args.copied_folder, foldername)
if filename.endswith('_problem.json'):
new_filename = filename[:-13] + '_popravljeno.json'
if os.path.exists(os.path.join(args.corrected_folder, corrected_files_mapper[foldername], new_filename)):
filename = new_filename
cf = os.path.join(args.corrected_folder, corrected_files_mapper[foldername], filename)
cor_files = read_json(cf)
ori_files = read_json(of)
target, source = compare_files(cor_files, ori_files)
if target or source:
if not os.path.exists(cpfol):
os.mkdir(cpfol)
shutil.copyfile(cf, cpf)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Read already processed xmls, erase entries without examples and limit gigafida examples to 1 per entry.')
parser.add_argument('--copied_folder', default='data/solar.svala.fixed.1.0.1',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--corrected_folder', default='data/solar.svala.1.0.1.corrected',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--original_folder', default='data/solar.svala1.0.1.original',
help='input file in (gz or xml currently). If none, then just database is loaded')
args = parser.parse_args()
start = time.time()
main(args)
logging.info("TIME: {}".format(time.time() - start))

@ -0,0 +1,164 @@
import argparse
import json
import logging
import os
import re
import time
problematic_words = ['...', '-', '', '"', "'"]
left_word = [',', '.', '!', '?', ':', ';', ')', '']
right_word = ['(', '']
ok_words = []
def read_json(file):
jf = open(file)
svala_data = json.load(jf)
jf.close()
return svala_data
def compare_files(corrected_file, original_file):
# count_differences(corrected_file['source'], original_file['source'])
target = False
source = False
source_modifications = 0
for corrected_source, original_source in zip(corrected_file['source'], original_file['source']):
if corrected_source != original_source:
source_modifications += 1
target_modifications = 0
for corrected_target, original_target in zip(corrected_file['target'], original_file['target']):
if corrected_target != original_target:
target_modifications += 1
if target_modifications > 0:
target = True
if source_modifications > 0:
source = True
return target, source
def mine_text(cor_files):
text = ''
has_space = False
is_problematic = False
errors = []
left_asterix = 0
right_asterix = 0
for corrected_source in cor_files:
word = corrected_source['text'].strip()
if re.match("^[a-zA-Z0-9ČĆŽŠĐčćžšđ§]+$", word):
if has_space:
text += ' '
text += word
has_space = True
elif word in problematic_words:
if has_space:
text += ' '
text += word
is_problematic = True
has_space = True
elif word in left_word:
if word == '':
left_asterix += 1
text += word
has_space = True
elif word in right_word:
if word == '':
right_asterix += 1
if has_space:
text += ' '
text += word
has_space = False
else:
if has_space:
text += ' '
text += word
is_problematic = True
has_space = True
errors.append(word)
if left_asterix != right_asterix:
is_problematic = True
if len(text) > 0 and text[-1] == ' ':
text = text[:-1]
return text, is_problematic, errors
def write_file(is_problematic, foldername, filename, text, is_target):
if is_target:
new_filename = filename[:-5] + '_target.json'
else:
new_filename = filename[:-5] + '_source.json'
if is_problematic:
folder_path = os.path.join(args.problematic_folder, foldername)
file_path = os.path.join(args.problematic_folder, foldername, new_filename)
else:
folder_path = os.path.join(args.unproblematic_folder, foldername)
file_path = os.path.join(args.unproblematic_folder, foldername, new_filename)
if not os.path.exists(folder_path):
os.mkdir(folder_path)
with open(file_path, 'w') as wf:
wf.write(text)
def main(args):
errors_count = 0
all_errors = set()
# create mapper to corrected files
corrected_files_mapper = {}
for foldername in os.listdir(args.corrected_folder):
orig_name = 'KUS' + foldername.split('KUS')[1]
corrected_files_mapper[orig_name] = foldername
for foldername in os.listdir(args.original_folder):
for filename in os.listdir(os.path.join(args.original_folder, foldername)):
of = os.path.join(args.original_folder, foldername, filename)
if filename.endswith('_problem.json'):
new_filename = filename[:-13] + '_popravljeno.json'
if os.path.exists(os.path.join(args.corrected_folder, corrected_files_mapper[foldername], new_filename)):
filename = new_filename
cf = os.path.join(args.corrected_folder, corrected_files_mapper[foldername], filename)
cor_files = read_json(cf)
ori_files = read_json(of)
target, source = compare_files(cor_files, ori_files)
if target:
text, is_problematic, errors = mine_text(cor_files['target'])
write_file(is_problematic, foldername, filename, text, True)
for er in errors:
all_errors.add(er)
errors_count += 1
if source:
text, is_problematic, errors = mine_text(cor_files['source'])
write_file(is_problematic, foldername, filename, text, False)
for er in errors:
all_errors.add(er)
errors_count += 1
print(corrected_files_mapper[foldername] + '/' + filename)
print(errors_count)
print(all_errors)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Read already processed xmls, erase entries without examples and limit gigafida examples to 1 per entry.')
parser.add_argument('--unproblematic_folder', default='data/svala_generated_text/unproblematic',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--problematic_folder', default='data/svala_generated_text/problematic',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--corrected_folder', default='data/solar.svala.1.0.1.corrected',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--original_folder', default='data/solar.svala1.0.1.original',
help='input file in (gz or xml currently). If none, then just database is loaded')
args = parser.parse_args()
start = time.time()
main(args)
logging.info("TIME: {}".format(time.time() - start))

@ -0,0 +1,83 @@
import argparse
import json
import logging
import os
import time
from xml.etree import ElementTree
def read_json(file):
jf = open(file)
svala_data = json.load(jf)
jf.close()
return svala_data
# def count_differences(corrected_input, original_input):
# modifications = 0
# corrected_dict = {el['id']: el['text'] for el in corrected_input}
# original_dict = {el['id']: el['text'] for el in original_input}
# a = sorted(corrected_dict)
# corrected_dict = dict(sorted(corrected_dict.items(), key=lambda item: int(item[0][1:])))
# original_dict = dict(sorted(original_dict.items(), key=lambda item: int(item[0][1:])))
# for corrected_source, original_source in zip(corrected_input['source'], original_file['source']):
# if corrected_source != original_source:
# modifications += 1
#
# return modifications
def compare_files(corrected_file, original_file):
# count_differences(corrected_file['source'], original_file['source'])
source_modifications = 0
for corrected_source, original_source in zip(corrected_file['source'], original_file['source']):
if corrected_source != original_source:
source_modifications += 1
target_modifications = 0
for corrected_target, original_target in zip(corrected_file['target'], original_file['target']):
if corrected_target != original_target:
target_modifications += 1
if target_modifications > 0 or source_modifications > 0:
return True
return False
def main(args):
# create mapper to corrected files
corrected_files_mapper = {}
for foldername in os.listdir(args.corrected_folder):
orig_name = 'KUS' + foldername.split('KUS')[1]
corrected_files_mapper[orig_name] = foldername
for foldername in os.listdir(args.original_folder):
for filename in os.listdir(os.path.join(args.original_folder, foldername)):
of = os.path.join(args.original_folder, foldername, filename)
if filename.endswith('_problem.json'):
new_filename = filename[:-13] + '_popravljeno.json'
if os.path.exists(os.path.join(args.corrected_folder, corrected_files_mapper[foldername], new_filename)):
filename = new_filename
cf = os.path.join(args.corrected_folder, corrected_files_mapper[foldername], filename)
if compare_files(read_json(cf), read_json(of)):
print(corrected_files_mapper[foldername] + '/' + filename)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Read already processed xmls, erase entries without examples and limit gigafida examples to 1 per entry.')
parser.add_argument('--corrected_folder', default='data/solar.svala.1.0.1.corrected.small',
help='input file in (gz or xml currently). If none, then just database is loaded')
parser.add_argument('--original_folder', default='data/solar.svala.1.0.1.original.small',
help='input file in (gz or xml currently). If none, then just database is loaded')
# parser.add_argument('--corrected_folder', default='data/solar.svala.1.0.1.corrected',
# help='input file in (gz or xml currently). If none, then just database is loaded')
# parser.add_argument('--original_folder', default='data/solar.svala1.0.1.original',
# help='input file in (gz or xml currently). If none, then just database is loaded')
args = parser.parse_args()
start = time.time()
main(args)
logging.info("TIME: {}".format(time.time() - start))
Loading…
Cancel
Save