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1208 lines
56 KiB
1208 lines
56 KiB
import argparse
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import json
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import logging
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import os
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import shutil
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import time
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from xml.etree import ElementTree
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from conllu import TokenList
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import conllu
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import classla
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import copy
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from classla.pipeline.tokenize_processor import TokenizeProcessor
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from lxml import etree
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from src.create_tei import construct_sentence_from_list, \
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construct_paragraph_from_list, TeiDocument, build_tei_etrees, build_links, build_complete_tei, convert_bibl
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logging.basicConfig(level=logging.INFO)
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def add_source(svala_i, source_i, sentence_string_id_split, source, el):
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source_id = "s" + svala_i
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source_token_id = f'{sentence_string_id_split[0]}s.{".".join(sentence_string_id_split[1:])}.{source_i}'
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token_tag = 'w' if el.tag.startswith('w') else 'pc'
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source.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'id': source_token_id,
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'space_after': False, 'svala_id': source_id})
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def add_target(svala_i, target_i, sentence_string_id_split, target, el):
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target_id = "t" + svala_i
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target_token_id = f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}.{target_i}'
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token_tag = 'w' if el.tag.startswith('w') else 'pc'
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target.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'id': target_token_id,
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'space_after': False, 'svala_id': target_id})
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def add_edges(source_id, target_id, svala_data, edges, source_token_id, target_token_id):
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edge_id = "e-" + source_id + "-" + target_id
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labels = svala_data['edges'][edge_id]['labels']
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edges.append({'source_ids': [source_token_id], 'target_ids': [target_token_id], 'labels': labels})
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def create_edges_list(target_ids, links_ids_mapper):
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target_edges = []
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target_edges_set = []
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for target_sentence in target_ids:
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target_sentence_edges = []
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for target_id in target_sentence:
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target_sentence_edges.extend(links_ids_mapper[target_id])
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target_edges.append(target_sentence_edges)
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target_edges_set.append(set(target_sentence_edges))
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return target_edges, target_edges_set
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SKIP_IDS = ['solar2284s.1.1.1']
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def create_edges(svala_data, source_par, target_par):
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# if source_par and source_par[0]:
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# if source_par[0][0]['id'] in SKIP_IDS:
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# return []
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# # print(source_par[0][0]['id'])
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# if source_par[0][0]['id'] == 'solar2440s.5.1.1':
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# print('pause!')
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# if target_par and target_par[0]:
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# print(target_par[0][0]['id'])
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# if target_par[0][0]['id'] == 'solar364t.5.1.1':
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# print('pause!')
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source_mapper = {el['svala_id']: el['id'] for source in source_par for el in source}
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target_mapper = {el['svala_id']: el['id'] for target in target_par for el in target}
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# source_ids = [el['svala_id'] for source in source_par for el in source]
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# target_ids = [el['svala_id'] for target in target_par for el in target]
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source_ids = [[el['svala_id'] for el in source] for source in source_par]
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target_ids = [[el['svala_id'] for el in target] for target in target_par]
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source_sentence_ids = [set([el['svala_id'] for el in source]) for source in source_par]
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target_sentence_ids = [set([el['svala_id'] for el in target]) for target in target_par]
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# create links to ids mapper
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links_ids_mapper = {}
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edges_of_one_type = set()
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# delete empty edge
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if 'e-' in svala_data['edges']:
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del (svala_data['edges']['e-'])
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for k, v in svala_data['edges'].items():
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has_source = False
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has_target = False
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for el in v['ids']:
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# create edges of one type
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if el[0] == 's':
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has_source = True
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if el[0] == 't':
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has_target = True
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# create links_ids_mapper
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if el not in links_ids_mapper:
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links_ids_mapper[el] = []
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links_ids_mapper[el].append(k)
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if not has_source or not has_target or (len(svala_data['source']) == 1 and svala_data['source'][0]['text'] == ' ') \
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or (len(svala_data['target']) == 1 and svala_data['target'][0]['text'] == ' '):
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edges_of_one_type.add(k)
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# delete edge with space
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save_deleted_edges = {}
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if len(svala_data['source']) == 1 and svala_data['source'][0]['text'] == ' ':
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for edg in links_ids_mapper[svala_data['source'][0]['id']]:
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save_deleted_edges[edg] = svala_data['edges'][edg]
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del (svala_data['edges'][edg])
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del (links_ids_mapper[svala_data['source'][0]['id']])
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if len(svala_data['target']) == 1 and svala_data['target'][0]['text'] == ' ':
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for edg in links_ids_mapper[svala_data['target'][0]['id']]:
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save_deleted_edges[edg] = svala_data['edges'][edg]
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del (svala_data['edges'][edg])
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del (links_ids_mapper[svala_data['target'][0]['id']])
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# create edge order
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edges_order = []
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edges_processed = set()
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# active_source_sentence_i = 0
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active_target_sentence_i = 0
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s_i = 0
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t_i = 0
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# create target edges
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target_edges, target_edges_set = create_edges_list(target_ids, links_ids_mapper)
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source_edges, source_edges_set = create_edges_list(source_ids, links_ids_mapper)
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last_target_edge = ''
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for active_source_sentence_i, active_source_sentence in enumerate(source_edges):
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for source_edge in active_source_sentence:
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print(source_edge)
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# if 'e-s261-t261' == source_edge:
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# print('aaa')
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# if 'e-s253-s254-s255-s256-s257-s258-s259-s260' == source_edge:
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# print('aaa')
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# if 'e-s252-t252' == source_edge:
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# print('aaa')
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if source_edge in edges_of_one_type:
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if source_edge not in edges_processed:
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edges_order.append(source_edge)
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edges_processed.add(source_edge)
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elif target_edges_set and source_edge in target_edges_set[active_target_sentence_i]:
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# if 'e-s120-t121' == source_edge:
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# print('aaa')
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# if 'e-s119-t119' == source_edge:
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# print('aaa')
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if source_edge not in edges_processed:
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edges_order.append(source_edge)
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edges_processed.add(source_edge)
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last_target_edge = source_edge
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# when source is connected to two targets
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elif source_edge not in target_edges_set[active_target_sentence_i]:
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# add missing edges from target
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while source_edge not in target_edges_set[active_target_sentence_i]:
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for target_edge in target_edges[active_target_sentence_i]:
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if target_edge in edges_of_one_type:
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if target_edge not in edges_processed:
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edges_order.append(target_edge)
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edges_processed.add(target_edge)
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# if 'e-s411-s412-t413' == target_edge:
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# print('nnnno')
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last_target_edge = target_edge
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active_target_sentence_i += 1
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# if active_target_sentence_i >= len(target_edges_set):
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# break
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if source_edge in target_edges_set[active_target_sentence_i]:
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if source_edge not in edges_processed:
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edges_order.append(source_edge)
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edges_processed.add(source_edge)
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else:
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raise 'Impossible!!!'
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if not target_edges_set or not target_edges_set[0] or active_target_sentence_i >= len(target_edges):
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continue
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# if last_target_edge == 'e-s197-t197':
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# print('HERE!')
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if len(target_edges[active_target_sentence_i]) == 0:
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active_target_sentence_i += 1
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continue
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# if last_target_edge == target_edges[active_target_sentence_i][-1] or (len(target_edges[active_target_sentence_i]) > 1 and last_target_edge == target_edges[active_target_sentence_i][-2] and target_edges[active_target_sentence_i][-1] in edges_of_one_type):
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# (target_edges[active_target_sentence_i][-1] in edges_of_one_type or (target_edges[active_target_sentence_i][-1] not in edges_of_one_type and target_edges[active_target_sentence_i][-1] not in source_edges_set[active_source_sentence_i]))
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# if last_target_edge == target_edges[active_target_sentence_i][-1] or (len(target_edges[active_target_sentence_i]) > 1 and last_target_edge == target_edges[active_target_sentence_i][-2] and last_target_edge in target_edges_set[active_target_sentence_i]):
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if last_target_edge == target_edges[active_target_sentence_i][-1] or (len(target_edges[active_target_sentence_i]) > 1 and last_target_edge == target_edges[active_target_sentence_i][-2] and (target_edges[active_target_sentence_i][-1] in edges_of_one_type or (target_edges[active_target_sentence_i][-1] not in edges_of_one_type and target_edges[active_target_sentence_i][-1] in source_edges_set[active_source_sentence_i]))):
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for target_edge in target_edges[active_target_sentence_i]:
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if target_edge in edges_of_one_type:
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if target_edge not in edges_processed:
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edges_order.append(target_edge)
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edges_processed.add(target_edge)
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# if 'e-s243-t243' == target_edge:
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# print('nnnno')
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last_target_edge = target_edge
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active_target_sentence_i += 1
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continue
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target_edge_in_next_source_edge_sentence = False
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for target_edge in target_edges[active_target_sentence_i]:
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if active_source_sentence_i + 1 < len(source_edges_set) and target_edge in source_edges_set[active_source_sentence_i + 1]:
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target_edge_in_next_source_edge_sentence = True
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break
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if target_edge_in_next_source_edge_sentence:
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pass
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elif not target_edge_in_next_source_edge_sentence:
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target_edge_in_next_source_edge_sentence = False
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while not target_edge_in_next_source_edge_sentence:
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# if active_target_sentence_i >= len(target_edges_set):
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# break
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for target_edge in target_edges[active_target_sentence_i]:
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if target_edge in edges_of_one_type:
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if target_edge not in edges_processed:
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edges_order.append(target_edge)
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edges_processed.add(target_edge)
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last_target_edge = target_edge
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# if there is no next source sentence
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if active_source_sentence_i + 1 >= len(source_edges_set):
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target_edge_in_next_source_edge_sentence = True
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# if last_target_edge only in target stop regularly
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if last_target_edge == target_edges[active_target_sentence_i][-1]:
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target_edge_in_next_source_edge_sentence = True
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# test if target_edge in next source
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for target_edge in target_edges[active_target_sentence_i]:
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if active_source_sentence_i + 1 < len(source_edges_set) and target_edge in source_edges_set[
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active_source_sentence_i + 1]:
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target_edge_in_next_source_edge_sentence = True
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break
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active_target_sentence_i += 1
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if not source_edges:
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for active_target_sentence in target_edges:
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for target_edge in active_target_sentence:
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if target_edge not in edges_processed:
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edges_order.append(target_edge)
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edges_processed.add(target_edge)
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# # create edge order
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# edges_order = []
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# edges_processed = set()
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# s_i = 0
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# t_i = 0
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# check_s_i = True
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# while s_i < len(source_ids) or t_i < len(target_ids):
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# # take care of getting ids over desired s_i/t_i
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# if check_s_i and s_i >= len(source_ids):
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# check_s_i = False
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#
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# if not check_s_i and t_i >= len(target_ids):
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# check_s_i = True
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#
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# if check_s_i:
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# id_of_interest = source_ids[s_i]
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# s_i += 1
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# check_s_i = not check_s_i
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# else:
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# id_of_interest = target_ids[t_i]
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# t_i += 1
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# check_s_i = not check_s_i
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#
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# any_addition = False
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# if id_of_interest not in links_ids_mapper:
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# print('NOOOOO')
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# for edge_id in links_ids_mapper[id_of_interest]:
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# if edge_id not in edges_processed:
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# if edge_id not in edges_of_one_type:
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# any_addition = True
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# edges_order.append(edge_id)
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# edges_processed.add(edge_id)
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# if not any_addition:
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# check_s_i = not check_s_i
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# # DEBUG stuff
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# for edge_order in edges_order:
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# if edges_order.count(edge_order) > 1:
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# # if edge_order not in a:
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# print(f'ERROR {edge_order}')
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#
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# for edge_order in edges_order:
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# if edge_order not in svala_data['edges']:
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# print(f'ERROR {edge_order}')
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#
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# for key in svala_data['edges'].keys():
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# if key not in edges_order:
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# print(f'ERROR {key}')
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#
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# a = len(svala_data['edges'])
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# b = len(edges_order)
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if len(svala_data['edges']) != len(edges_order):
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for k, v in save_deleted_edges.items():
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svala_data['edges'][k] = v
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assert len(svala_data['edges']) == len(edges_order)
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sentence_edges = []
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source_sent_id = 0
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target_sent_id = 0
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# actually add edges
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edges = []
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for edge_id in edges_order:
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labels = svala_data['edges'][edge_id]['labels']
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source_ids = [source_mapper[el] for el in svala_data['edges'][edge_id]['ids'] if el in source_mapper]
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target_ids = [target_mapper[el] for el in svala_data['edges'][edge_id]['ids'] if el in target_mapper]
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ids = svala_data['edges'][edge_id]['ids']
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source_ok = [el[0] == 't' or el in source_sentence_ids[source_sent_id] for el in ids] if source_sentence_ids else []
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source_ok_all = all(source_ok)
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if not source_ok_all:
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source_sent_id += 1
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if edge_id == 'e-s590-t590':
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print(edge_id)
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target_ok = [el[0] == 's' or el in target_sentence_ids[target_sent_id] for el in ids] if target_sentence_ids else []
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target_ok_all = all(target_ok)
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if not target_ok_all:
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target_sent_id += 1
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if not source_ok_all or not target_ok_all:
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sentence_edges.append(edges)
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edges = []
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edges.append({'source_ids': source_ids, 'target_ids': target_ids, 'labels': labels})
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if edges:
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sentence_edges.append(edges)
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return sentence_edges
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def add_token(svala_i, source_i, target_i, el, source, target, edges, svala_data, sentence_string_id):
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source_id = "s" + svala_i
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target_id = "t" + svala_i
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edge_id = "e-" + source_id + "-" + target_id
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labels = svala_data['edges'][edge_id]['labels']
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sentence_string_id_split = sentence_string_id.split('.')
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source_token_id = f'{sentence_string_id_split[0]}s.{".".join(sentence_string_id_split[1:])}.{source_i}'
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target_token_id = f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}.{target_i}'
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token_tag = 'w' if el.tag.startswith('w') else 'pc'
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lemma = el.attrib['lemma'] if token_tag == 'w' else el.text
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source.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'lemma': lemma, 'id': source_token_id, 'space_after': False, 'svala_id': source_id})
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target.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'lemma': lemma, 'id': target_token_id, 'space_after': False, 'svala_id': target_id})
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edges.append({'source_ids': [source_token_id], 'target_ids': [target_token_id], 'labels': labels})
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def add_error_token(el, out_list, sentence_string_id, out_list_i, out_list_ids, is_source, s_t_id):
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sentence_string_id_split = sentence_string_id.split('.')
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source_token_id = f'{sentence_string_id_split[0]}s.{".".join(sentence_string_id_split[1:])}.{out_list_i}' if is_source \
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else f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}.{out_list_i}'
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token_tag = 'w' if el.tag.startswith('w') else 'pc'
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lemma = el.attrib['lemma'] if token_tag == 'w' else el.text
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out_list.append({'token': el.text, 'tag': token_tag, 'ana': el.attrib['ana'], 'lemma': lemma, 'id': source_token_id, 'space_after': False, 'svala_id': s_t_id})
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out_list_ids.append(source_token_id)
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def add_error_token_source_target_only(el, out_list, sentence_string_id, out_list_i, is_source, s_t_id):
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sentence_string_id_split = sentence_string_id.split('.')
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source_token_id = f'{sentence_string_id_split[0]}s.{".".join(sentence_string_id_split[1:])}.{out_list_i}' if is_source \
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else f'{sentence_string_id_split[0]}t.{".".join(sentence_string_id_split[1:])}.{out_list_i}'
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token_tag = 'w' if el.tag.startswith('w') else 'pc'
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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})
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def add_errors1_0_1(svala_i, source_i, target_i, error, source, target, svala_data, sentence_string_id, edges=None):
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source_edge_ids = []
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target_edge_ids = []
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source_ids = []
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target_ids = []
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# solar5.7
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for el in error:
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if el.tag.startswith('w') or el.tag.startswith('pc'):
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ind = str(svala_i)
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source_id = "s" + ind
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|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el, source, sentence_string_id, source_i, source_ids, 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
|
|
target_edge_ids.append(target_id)
|
|
|
|
add_error_token(p_el, target, sentence_string_id, target_i, target_ids, 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
|
|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el_l2, source, sentence_string_id, source_i, source_ids, 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
|
|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el_l3, source, sentence_string_id, source_i, source_ids, 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
|
|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el_l4, source, sentence_string_id, source_i, source_ids, 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
|
|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el_l5, source, sentence_string_id, source_i, source_ids, 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
|
|
target_edge_ids.append(target_id)
|
|
|
|
add_error_token(p_el, target, sentence_string_id, target_i, target_ids, False, target_id)
|
|
|
|
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 = []
|
|
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_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
|
|
target_edge_ids.append(target_id)
|
|
|
|
add_error_token(p_el, target, sentence_string_id, target_i, target_ids, 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
|
|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el_l2, source, sentence_string_id, source_i, source_ids, 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
|
|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el_l3, source, sentence_string_id, source_i, source_ids, 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
|
|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el_l4, source, sentence_string_id, source_i, source_ids, 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
|
|
source_edge_ids.append(source_id)
|
|
|
|
add_error_token(el_l5, source, sentence_string_id, source_i, source_ids, 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
|
|
# 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_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
|
|
|
|
|
|
def create_conllu(interest_list, sentence_string_id):
|
|
conllu_result = TokenList([{"id": token_i + 1, "form": token['token'], "lemma": None, "upos": None, "xpos": None, "feats": None,
|
|
"head": None, "deprel": None, "deps": None, "misc": "SpaceAfter=No"} if not token['space_after']
|
|
else {"id": token_i + 1, "form": token['token'], "lemma": None, "upos": None, "xpos": None,
|
|
"feats": None, "head": None, "deprel": None, "deps": None, "misc": None} for token_i, token in
|
|
enumerate(interest_list)])
|
|
# Delete last SpaceAfter
|
|
misc = conllu_result[len(conllu_result) - 1]['misc'] if len(conllu_result) > 0 else None
|
|
if misc is not None:
|
|
misc_split = misc.split('|')
|
|
if misc is not None and misc == 'SpaceAfter=No':
|
|
conllu_result[len(conllu_result) - 1]['misc'] = None
|
|
elif misc is not None and 'SpaceAfter=No' in misc_split:
|
|
conllu_result[len(conllu_result) - 1]['misc'] = '|'.join([el for el in misc_split if el != 'SpaceAfter=No'])
|
|
conllu_result.metadata = {"sent_id": sentence_string_id}
|
|
|
|
return conllu_result.serialize()
|
|
|
|
|
|
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 = []
|
|
|
|
par_source = []
|
|
par_target = []
|
|
|
|
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)
|
|
elif el.tag.startswith('c'):
|
|
if len(source) > 0:
|
|
source[-1]['space_after'] = True
|
|
if len(target) > 0:
|
|
target[-1]['space_after'] = True
|
|
|
|
par_source.append(source)
|
|
par_target.append(target)
|
|
|
|
# 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
|
|
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, complete_source_conllu, complete_target_conllu
|
|
|
|
|
|
def read_raw_text(path):
|
|
with open(path, 'r') as rf:
|
|
return rf.read()
|
|
|
|
HAND_FIXES = {'§§§pisala': ['§', '§', '§', 'pisala'], '§§§poldne': ['§', '§', '§', 'poldne'], '§§§o': ['§', '§', '§', 'o'], '§§§mimi': ['§', '§', '§', 'mimi'], '§§§nil': ['§', '§', '§', 'nil'], '§§§ela': ['§', '§', '§', 'ela'], 'sam§§§': ['sam', '§', '§', '§'], 'globa觧§': ['globač', '§', '§', '§'], 'sin.': ['sin', '.'], '§§§oveduje': ['§', '§', '§', 'oveduje'], 'na§§§': ['na', '§', '§', '§'], '§§§ka§§§': ['§', '§', '§', 'ka', '§', '§', '§'], '§§§e§§§': ['§', '§', '§', 'e', '§', '§', '§'], '§§§': ['§', '§', '§'], 'ljubezni.': ['ljubezni', '.'], '12.': ['12', '.'], '16.': ['16', '.'], 'st.': ['st', '.'], 'S.': ['S', '.'], 'pr.': ['pr', '.'], 'n.': ['n', '.'], '19:30': ['19', ':', '30'], '9.': ['9', '.'], '6:35': ['6', ':', '35'], 'itd.': ['itd', '.'], 'Sv.': ['Sv', '.'], 'npr.': ['npr', '.'], 'sv.': ['sv', '.'], '12:00': ['12', ':', '00'], "sram'vali": ['sram', "'", 'vali'], '18:00': ['18', ':', '00'], 'J.': ['J', '.'], '5:45': ['5', ':', '45'], '17.': ['17', '.'], '9.00h': ['9', '.', '00h'], 'H.': ['H', '.'], '1.': ['1', '.'], '6.': ['6', '.'], '7:10': ['7', ':', '10'], 'g.': ['g', '.'], 'Oz.': ['Oz', '.'], '20:00': ['20', ':', '00'], '17.4.2010': ['17.', '4.', '2010'], 'ga.': ['ga', '.'], 'prof.': ['prof', '.'], '6:45': ['6', ':', '45'], '19.': ['19', '.'], '3.': ['3', '.'], 'tj.': ['tj', '.'], 'Prof.': ['Prof', '.'], '8.': ['8', '.'], '9:18': ['9', ':', '18'], 'ipd.': ['ipd', '.'], '7.': ['7', '.'], 'št.': ['št', '.'], 'oz.': ['oz', '.'], 'R.': ['R', '.'], '13:30': ['13', ':', '30'], '5.': ['5', '.']}
|
|
|
|
def map_svala_tokenized(svala_data_part, tokenized_paragraph):
|
|
paragraph_res = []
|
|
svala_data_i = 0
|
|
wierd_sign_count = 0
|
|
for sentence in tokenized_paragraph:
|
|
sentence_res = []
|
|
sentence_id = 0
|
|
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']:
|
|
key = svala_data_part[svala_data_i]['text'].strip()
|
|
if key not in HAND_FIXES:
|
|
print(f'key: {key} ; tok[text]: {tok["text"]}')
|
|
if key.startswith('§§§') and key.endswith('§§§'):
|
|
HAND_FIXES[key] = ['§', '§', '§', key[3:-3], '§', '§', '§']
|
|
elif key.startswith('§§§'):
|
|
HAND_FIXES[key] = ['§', '§', '§', key[3:]]
|
|
elif key.endswith('§§§'):
|
|
HAND_FIXES[key] = [key[:-3], '§', '§', '§']
|
|
else:
|
|
raise 'Word mismatch!'
|
|
|
|
if tok['text'] == HAND_FIXES[key][wierd_sign_count]:
|
|
wierd_sign_count += 1
|
|
if wierd_sign_count < len(HAND_FIXES[key]):
|
|
continue
|
|
else:
|
|
tok['text'] = key
|
|
wierd_sign_count = 0
|
|
else:
|
|
print(f'key: {key} ; tok[text]: {tok["text"]}')
|
|
raise 'Word mismatch!'
|
|
# if tok['text'] == '§' and svala_data_part[svala_data_i]['text'].strip() == '§§§':
|
|
# wierd_sign_count += 1
|
|
# if wierd_sign_count < 3:
|
|
# continue
|
|
# else:
|
|
# tok['text'] = '§§§'
|
|
# wierd_sign_count = 0
|
|
# else:
|
|
# raise 'Word mismatch!'
|
|
sentence_id += 1
|
|
sentence_res.append({'token': tok['text'], 'tag': tag, 'id': sentence_id, '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 map_svala_solar2(svala_data_part, solar2_paragraph):
|
|
paragraph_res = []
|
|
svala_data_i = 0
|
|
wierd_sign_count = 0
|
|
for sentence in solar2_paragraph:
|
|
sentence_res = []
|
|
sentence_id = 0
|
|
for tok in sentence:
|
|
# if svala_data_part[svala_data_i]['text'].strip() != tok['token']:
|
|
# if tok['text'] == '§' and svala_data_part[svala_data_i]['token'].strip() == '§§§':
|
|
# wierd_sign_count += 1
|
|
# if wierd_sign_count < 3:
|
|
# continue
|
|
# else:
|
|
# tok['text'] = '§§§'
|
|
# wierd_sign_count = 0
|
|
# else:
|
|
# raise 'Word mismatch!'
|
|
assert svala_data_part[svala_data_i]['text'].strip() == tok['token']
|
|
sentence_id += 1
|
|
tok['svala_id'] = svala_data_part[svala_data_i]['id']
|
|
svala_data_i += 1
|
|
|
|
|
|
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) if text else ([], [], [])
|
|
# 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) if text else ([], [], [])
|
|
target_res = map_svala_tokenized(svala_data['target'], target_tokenized)
|
|
|
|
# TODO RETURN IF SOURCE AND TARGET ARE NOT NONE
|
|
par_source = []
|
|
par_target = []
|
|
sentences_len = len(sentences)
|
|
if source_raw_text is not None:
|
|
sentences_len = max(sentences_len, len(source_res))
|
|
if target_raw_text is not None:
|
|
sentences_len = max(sentences_len, len(target_res))
|
|
for sentence_id in range(sentences_len):
|
|
# assert sentence_id < len(sentences)
|
|
|
|
# sentence_id += 1
|
|
# 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}'
|
|
sentence_string_id_split = sentence_string_id.split('.')
|
|
|
|
if sentence_id - 1 < len(sentences):
|
|
sentence = sentences[sentence_id - 1]
|
|
for el in sentence:
|
|
# if source_i == 101:
|
|
# print('HMM')
|
|
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)
|
|
par_source.append(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_target.append(target)
|
|
|
|
if source_raw_text is None:
|
|
par_source.append(source)
|
|
if target_raw_text is None:
|
|
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))
|
|
|
|
# reannotate svala_ids
|
|
if source_raw_text is None:
|
|
map_svala_solar2(svala_data['source'], par_source)
|
|
if target_raw_text is None:
|
|
map_svala_solar2(svala_data['target'], par_target)
|
|
|
|
sentence_edges = create_edges(svala_data, par_source, par_target)
|
|
|
|
return etree_source_sentences, etree_target_sentences, sentence_edges, complete_source_conllu, complete_target_conllu
|
|
|
|
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)
|
|
etree_source_documents = []
|
|
etree_target_documents = []
|
|
etree_source_divs = []
|
|
etree_target_divs = []
|
|
|
|
complete_source_conllu = ''
|
|
complete_target_conllu = ''
|
|
|
|
document_edges = []
|
|
filename_encountered = False
|
|
i = 0
|
|
folders_count = 5484
|
|
for div in et.iter('div'):
|
|
bibl = div.find('bibl')
|
|
file_name = bibl.get('n')
|
|
file_name = file_name.replace('/', '_')
|
|
print(f'{i*100/folders_count} % : {file_name}')
|
|
i += 1
|
|
# if file_name == 'S20-PI-slo-2-SG-D-2016_2017-30479-12.txt':
|
|
# if file_name == 'KUS-G-slo-1-LJ-E-2009_2010-10602':
|
|
if i*100/folders_count > 40:
|
|
filename_encountered = True
|
|
# if i*100/folders_count > 50:
|
|
# filename_encountered = False
|
|
if not filename_encountered:
|
|
continue
|
|
|
|
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
|
|
|
|
svala_list = [[fname[:-13], fname] if 'problem' in fname else [fname[:-5], fname] for fname in os.listdir(svala_path)]
|
|
svala_dict = {e[0]: e[1] for e in svala_list}
|
|
|
|
if os.path.exists(corrected_svala_path):
|
|
corrected_svala_list = [[fname[:-13], fname] if 'problem' in fname else [fname[:-5], fname] for fname in os.listdir(corrected_svala_path)]
|
|
corrected_svala_dict = {e[0]: e[1] for e in corrected_svala_list}
|
|
|
|
svala_dict.update(corrected_svala_dict)
|
|
|
|
etree_source_paragraphs = []
|
|
etree_target_paragraphs = []
|
|
paragraph_edges = []
|
|
|
|
paragraphs = div.findall('p')
|
|
for paragraph in paragraphs:
|
|
sentences = paragraph.findall('s')
|
|
svala_i = 1
|
|
|
|
# read json
|
|
# if paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'] == 'solar5.7':
|
|
# print('here')
|
|
svala_file = os.path.join(svala_path, svala_dict[paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id']])
|
|
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()
|
|
|
|
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'
|
|
|
|
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 not (source_raw_text or target_raw_text):
|
|
etree_source_sentences, etree_target_sentences, sentence_edges, complete_source_conllu, complete_target_conllu = process_solar2_paragraph(sentences, paragraph, svala_i, svala_data, add_errors_func, nlp,
|
|
complete_source_conllu, complete_target_conllu)
|
|
|
|
else:
|
|
etree_source_sentences, etree_target_sentences, sentence_edges, complete_source_conllu, complete_target_conllu = 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))
|
|
paragraph_edges.append(sentence_edges)
|
|
|
|
etree_bibl = convert_bibl(bibl)
|
|
|
|
etree_source_divs.append((etree_source_paragraphs, copy.deepcopy(etree_bibl)))
|
|
etree_target_divs.append((etree_target_paragraphs, copy.deepcopy(etree_bibl)))
|
|
document_edges.append(paragraph_edges)
|
|
|
|
print('APPENDING DOCUMENT...')
|
|
etree_source_documents.append(TeiDocument(paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'].split('.')[0] + 's', etree_source_divs))
|
|
etree_target_documents.append(TeiDocument(paragraph.attrib['{http://www.w3.org/XML/1998/namespace}id'].split('.')[0] + 't', etree_target_divs))
|
|
|
|
print('BUILDING TEI DOCUMENTS...')
|
|
etree_source = build_tei_etrees(etree_source_documents)
|
|
etree_target = build_tei_etrees(etree_target_documents)
|
|
|
|
print('BUILDING LINKS...')
|
|
etree_links = build_links(document_edges)
|
|
|
|
print('Writting all but complete')
|
|
with open(os.path.join(args.results_folder, f"source.conllu"), 'w') as sf:
|
|
sf.write(complete_source_conllu)
|
|
|
|
with open(os.path.join(args.results_folder, f"target.conllu"), 'w') as sf:
|
|
sf.write(complete_target_conllu)
|
|
|
|
with open(os.path.join(args.results_folder, f"source.xml"), 'w') as sf:
|
|
sf.write(etree.tostring(etree_source[0], pretty_print=True, encoding='utf-8').decode())
|
|
|
|
with open(os.path.join(args.results_folder, f"target.xml"), 'w') as tf:
|
|
tf.write(etree.tostring(etree_target[0], pretty_print=True, encoding='utf-8').decode())
|
|
|
|
with open(os.path.join(args.results_folder, f"links.xml"), 'w') as tf:
|
|
tf.write(etree.tostring(etree_links, pretty_print=True, encoding='utf-8').decode())
|
|
|
|
with open(os.path.join(args.results_folder, f"links.json"), 'w') as jf:
|
|
json.dump(document_edges, jf, ensure_ascii=False, indent=" ")
|
|
|
|
# TODO STUCKS HERE
|
|
print('COMPLETE TREE CREATION...')
|
|
complete_etree = build_complete_tei(copy.deepcopy(etree_source), copy.deepcopy(etree_target), etree_links)
|
|
|
|
print('WRITING FILES')
|
|
# with open(os.path.join(args.results_folder, f"source.conllu"), 'w') as sf:
|
|
# sf.write(complete_source_conllu)
|
|
#
|
|
# with open(os.path.join(args.results_folder, f"target.conllu"), 'w') as sf:
|
|
# sf.write(complete_target_conllu)
|
|
#
|
|
# with open(os.path.join(args.results_folder, f"source.xml"), 'w') as sf:
|
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# sf.write(etree.tostring(etree_source[0], pretty_print=True, encoding='utf-8').decode())
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#
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# with open(os.path.join(args.results_folder, f"target.xml"), 'w') as tf:
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# tf.write(etree.tostring(etree_target[0], pretty_print=True, encoding='utf-8').decode())
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#
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# with open(os.path.join(args.results_folder, f"links.xml"), 'w') as tf:
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# tf.write(etree.tostring(etree_links, pretty_print=True, encoding='utf-8').decode())
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with open(os.path.join(args.results_folder, f"complete.xml"), 'w') as tf:
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tf.write(etree.tostring(complete_etree, pretty_print=True, encoding='utf-8').decode())
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# with open(os.path.join(args.results_folder, f"links.json"), 'w') as jf:
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# json.dump(document_edges, jf, ensure_ascii=False, indent=" ")
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def main(args):
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with open(args.solar_file, 'r') as fp:
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logging.info(args.solar_file)
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nlp = classla.Pipeline('sl', pos_use_lexicon=True, pos_lemma_pretag=False, tokenize_pretokenized="conllu", type='standard_jos')
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nlp_tokenize = classla.Pipeline('sl', processors='tokenize', pos_lemma_pretag=True)
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et = ElementTree.XML(fp.read())
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process_file(et, args, nlp, nlp_tokenize)
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|
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(
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description='Read already processed xmls, erase entries without examples and limit gigafida examples to 1 per entry.')
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parser.add_argument('--solar_file', default='data/Solar2.0/solar2.xml',
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help='input file in (gz or xml currently). If none, then just database is loaded')
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parser.add_argument('--svala_folder', default='data/solar.svala',
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help='input file in (gz or xml currently). If none, then just database is loaded')
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parser.add_argument('--corrected_svala_folder', default='data/solar.svala.fixed.1.0.1_2',
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help='input file in (gz or xml currently). If none, then just database is loaded')
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parser.add_argument('--results_folder', default='data/results/solar3.0',
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help='input file in (gz or xml currently). If none, then just database is loaded')
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parser.add_argument('--svala_generated_text_folder', default='data/svala_generated_text.formatted',
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help='input file in (gz or xml currently). If none, then just database is loaded')
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parser.add_argument('--raw_conllu_interprocessing', default='data/processing.raw_conllu',
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help='input file in (gz or xml currently). If none, then just database is loaded')
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args = parser.parse_args()
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|
|
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start = time.time()
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main(args)
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logging.info("TIME: {}".format(time.time() - start))
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