def retrieve_query_doc(self):
for q in self.queries:
q_results = dict()
print(q.name + '...'),
found_doc_path = search(q.name, self.lucene_searcher, self.lucene_analyzer, 3000)
for doc_path in found_doc_path:
doc_id = doc_path.split('/')[-1].strip()
doc_content = io.open(doc_path, 'r', -1, 'utf-8').read()
if doc_content.replace(' ', '').replace('\n', '').count(q.name) < 4:
continue
q_results[doc_id] = doc_content
# clean doc
cleaned_doc = remove_doc_noise(doc_content) # remove tags like datetime, headline, dateline, etc.
cleaned_doc = remove_xml_tag(cleaned_doc)
cleaned_doc = remove_space_linebreak(cleaned_doc)
# create offset mapping table betwenn clean doc and origin doc
if doc_id in self.doc_mapping_table.keys():
continue
offset_mapping_table = OrderedDict()
cleaned_doc_index = 0
origin_doc_index = 0
for char in cleaned_doc:
while True:
if char != doc_content[origin_doc_index]:
origin_doc_index += 1
else:
offset_mapping_table[cleaned_doc_index] = origin_doc_index
cleaned_doc_index += 1
origin_doc_index += 1
break
# check correctness of offset mapping table
for index in offset_mapping_table.keys():
assert cleaned_doc[index] == doc_content[offset_mapping_table[index]]
self.doc_mapping_table[doc_id] = offset_mapping_table
self.cleaned_docs[doc_id] = cleaned_doc
self.query_docs[q.id] = q_results
print('Done')
def general_inference(query_system_answer):
# load sf source document
if version == 'ldc':
src_doc = load_sf_src_doc(
'../../data/LDC/LDC2014E123_TAC_KBP_2014_Chinese_Regular_Slot_Filling_Training_Data/'
'data/source_doc/')
elif version == 'eval':
src_doc = load_sf_src_doc(
'../../data/LDC/KBP_2015_Chinese_Regular_Slot_Filling_Evaluation_Data/source_doc/'
)
# ================== remove slot filler related to 记者 ===================== #
for slot_type in query_system_answer.output.keys():
line_outputs = query_system_answer.output[slot_type]
corrected_line_outputs = []
for l in line_outputs:
if not l.slot_filler:
corrected_line_outputs.append(l)
continue
void_l = False
for w_p in l.wide_provenance:
w_p_text = src_doc[w_p.doc_id][w_p.beg:w_p.end]
if (u'记者' + l.slot_filler) in w_p_text or (
l.slot_filler + u'记者') in w_p_text:
void_l = True
break
if void_l is False:
corrected_line_outputs.append(l)
query_system_answer.output[slot_type] = corrected_line_outputs
# ================== fix slot filler offset ===================== #
for slot_type in query_system_answer.output.keys():
if 'date' in slot_type:
continue
line_outputs = query_system_answer.output[slot_type]
for l in line_outputs:
if not l.slot_filler:
continue
for i in xrange(len(l.slot_filler_prov)):
try:
s_p = l.slot_filler_prov[i]
s_p_text = src_doc[s_p.doc_id][s_p.beg:s_p.end + 1]
if l.slot_filler == remove_space_linebreak(s_p_text):
continue
w_p = l.wide_provenance[i]
w_p_text = src_doc[w_p.doc_id][w_p.beg:w_p.end + 1]
correct_w_p_index = src_doc[w_p.doc_id].find(w_p_text)
s_p_inner_index = w_p_text.find(l.slot_filler)
correct_s_p_beg = correct_w_p_index + s_p_inner_index
correct_s_p_end = correct_s_p_beg + len(
l.slot_filler) - 1
corrected_s_p_text = src_doc[
s_p.doc_id][correct_s_p_beg:correct_s_p_end + 1]
if corrected_s_p_text != l.slot_filler:
continue
l.slot_filler_prov[i].beg = correct_s_p_beg
l.slot_filler_prov[i].end = correct_s_p_end
except IndexError:
continue
return query_system_answer
def general_inference(query_system_answer):
# load sf source document
if version == 'ldc':
src_doc = load_sf_src_doc('../../data/LDC/LDC2014E123_TAC_KBP_2014_Chinese_Regular_Slot_Filling_Training_Data/'
'data/source_doc/')
elif version == 'eval':
src_doc = load_sf_src_doc('../../data/LDC/KBP_2015_Chinese_Regular_Slot_Filling_Evaluation_Data/source_doc/')
# ================== remove slot filler related to 记者 ===================== #
for slot_type in query_system_answer.output.keys():
line_outputs = query_system_answer.output[slot_type]
corrected_line_outputs = []
for l in line_outputs:
if not l.slot_filler:
corrected_line_outputs.append(l)
continue
void_l = False
for w_p in l.wide_provenance:
w_p_text = src_doc[w_p.doc_id][w_p.beg:w_p.end]
if (u'记者' + l.slot_filler) in w_p_text or (l.slot_filler + u'记者') in w_p_text:
void_l = True
break
if void_l is False:
corrected_line_outputs.append(l)
query_system_answer.output[slot_type] = corrected_line_outputs
# ================== fix slot filler offset ===================== #
for slot_type in query_system_answer.output.keys():
if 'date' in slot_type:
continue
line_outputs = query_system_answer.output[slot_type]
for l in line_outputs:
if not l.slot_filler:
continue
for i in xrange(len(l.slot_filler_prov)):
try:
s_p = l.slot_filler_prov[i]
s_p_text = src_doc[s_p.doc_id][s_p.beg:s_p.end+1]
if l.slot_filler == remove_space_linebreak(s_p_text):
continue
w_p = l.wide_provenance[i]
w_p_text = src_doc[w_p.doc_id][w_p.beg:w_p.end+1]
correct_w_p_index = src_doc[w_p.doc_id].find(w_p_text)
s_p_inner_index = w_p_text.find(l.slot_filler)
correct_s_p_beg = correct_w_p_index + s_p_inner_index
correct_s_p_end = correct_s_p_beg + len(l.slot_filler) - 1
corrected_s_p_text = src_doc[s_p.doc_id][correct_s_p_beg:correct_s_p_end+1]
if corrected_s_p_text != l.slot_filler:
continue
l.slot_filler_prov[i].beg = correct_s_p_beg
l.slot_filler_prov[i].end = correct_s_p_end
except IndexError:
continue
return query_system_answer
