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# -*- coding: utf-8 -*-
import sys
import io
import stanza
# nlp = stanza.Pipeline(lang='en', processors='tokenize,mwt,pos,lemma',package='craft') #package='craft'
nlp = stanza.Pipeline(lang='en', processors={'tokenize': 'spacy'},package='None') #package='craft'
REL_ENT={'arg1':'Species',
'arg2':'Gene'}
ENTITY_TAG={'arg1':['arg1s','arg1e'],
'arg2':['arg2s','arg2e'],
'gene':['gene1s','gene1e'],
'species':['species1s','species1e']
}
# ssplit token and revise index
def ssplit_token(infile):
fin=open(infile,'r',encoding='utf-8')
fout=io.StringIO()
all_in=fin.read().strip().split('\n\n')
fin.close()
for doc_text in all_in:
lines=doc_text.split('\n')
ori_text=lines[0].split('|t|')[1]+' '+lines[1].split('|a|')[1]
pmid=lines[0].split('|t|')[0]
# print(pmid)
entity_all=[] #[[seg0,seg1,...,],[]]
for i in range(2,len(lines)):
seg=lines[i].split('\t')
entity_all.append(seg)
#ssplit token
doc_stanza = nlp(ori_text)
token_text=''
for sent in doc_stanza.sentences:
for word in sent.words:
if word.text==' ':
pass
# print('token is blank!')
else:
token_text+=word.text+' '
#token_text=token_text+' ' #sentence split by four blank
#ori_index map token_index
index_map=[-1]*len(ori_text)
j=0
space_list=[' ',chr(160),chr(8201),chr(8194),chr(8197),chr(8202)] #空格有好几种，第一个是常用32,第二个shi 160,8201,8194,8197
for i in range(0,len(ori_text)):
if ori_text[i] in space_list:
pass
elif ori_text[i]==token_text[j]:
#if i>0 and i<285:
# print('=i,j:',i,j,ori_text[i-1:i+1],token_text[j-1:j+1])
index_map[i]=j
j+=1
else:
#if i==283:
# print('!i,j:',i,j,ori_text[i-1:i+1],token_text[j-1:j+1])
j+=1
temp_log=j
try:
while(ori_text[i]!=token_text[j]):
j+=1
except:
print('doc',doc_text)
print('token_text:',token_text)
print('error:',ori_text[i-10:i+10],'i:',ori_text[i],'j:',token_text[temp_log],',',token_text[temp_log-10:temp_log+10])
print(ord(ori_text[i]),ord(' '))
sys.exit()
index_map[i]=j
j+=1
# print(index_map)
# token_text=token_text.replace(' ','<EOS>')
# print(token_text)
fout.write(token_text+'\n')
for ele in entity_all:
if index_map[int(ele[1])]==-1:
new_ents=index_map[int(ele[1])+1]
else:
new_ents=index_map[int(ele[1])]
if index_map[int(ele[2])-1]==-1:
new_ente=index_map[int(ele[2])-1-1]+1
else:
new_ente=index_map[int(ele[2])-1]+1
new_ent=token_text[new_ents:new_ente]
if ele[4]=='Species' or ele[4]=='Gene':
fout.write(ele[0]+'\t'+str(new_ents)+'\t'+str(new_ente)+'\t'+new_ent+'\t'+ele[4]+'\t'+ele[5]+'\n')
else:
# print(ele[4])
fout.write(ele[0]+'\t'+str(new_ents)+'\t'+str(new_ente)+'\t'+new_ent+'\t'+'Gene'+'\t'+ele[5]+'\n')
fout.write('\n')
return fout.getvalue()
def corpus_noNest(token_input):
fin=io.StringIO(token_input)
fout=io.StringIO()
documents=fin.read().strip().split('\n\n')
fin.close()
total_entity=0
over_entity=0
nest_entity=0
for doc in documents:
lines=doc.split('\n')
context=lines[0]
entity_list=[]
if len(lines)>1:
doc_result={}
for i in range(1,len(lines)):
segs=lines[i].split('\t')
doc_result[lines[i]]=[int(segs[1]),int(segs[2])]
doc_result=sorted(doc_result.items(), key=lambda kv:(kv[1]), reverse=False)
doc_result_sort=[]
for ele in doc_result:
doc_result_sort.append(ele[0])
first_entity=doc_result_sort[0].split('\t')
nest_list=[first_entity]
max_eid=int(first_entity[2])
total_entity+=len(lines)-2
for i in range(1,len(doc_result_sort)):
segs=doc_result_sort[i].split('\t')
if int(segs[1])> max_eid:
if len(nest_list)==1:
entity_list.append(nest_list[0])
nest_list=[]
nest_list.append(segs)
if int(segs[2])>max_eid:
max_eid=int(segs[2])
else:
# print(nest_list)
nest_entity+=len(nest_list)-1
tem=find_max_entity(nest_list,context)#find max entity
# if len(tem)>1:
# print('max nest >1:',tem)
entity_list.extend(tem)
nest_list=[]
nest_list.append(segs)
if int(segs[2])>max_eid:
max_eid=int(segs[2])
else:
nest_list.append(segs)
over_entity+=1
if int(segs[2])>max_eid:
max_eid=int(segs[2])
if nest_list!=[]:
if len(nest_list)==1:
entity_list.append(nest_list[0])
else:
tem=find_max_entity(nest_list,context)#find max entity
# if len(tem)>1:
# print('max nest >1:',tem)
entity_list.extend(tem)
fout.write(context+'\n')
for ele in entity_list:
if ele[4]=='Gene':
temp_gene={}
gene_ids=ele[5].split(',')
for gene_id in gene_ids:
temp_id=gene_id[gene_id.find('Species:'):-1]
spe_id=temp_id[len('Species:'):]
temp_gene[temp_id]=int(spe_id)
temp_gene_sort=sorted(temp_gene.items(), key=lambda kv:(kv[1]), reverse=False)
final_gene_id=''
for temp_ele in temp_gene_sort:
final_gene_id+=temp_ele[0]+','
fout.write('\t'.join(ele[:-1])+'\t'+final_gene_id[:-1]+'\n')
else:
fout.write('\t'.join(ele)+'\n')
fout.write('\n')
# print(total_entity,over_entity, nest_entity)
return fout.getvalue()
def find_max_entity(nest_list,text):
max_len=0
final_tem=[]
max_index=0
for i in range(0, len(nest_list)):
if nest_list[i][4] =='Species':
final_tem.append(nest_list[i])
else:
cur_len=int(nest_list[i][2])-int(nest_list[i][1])
if cur_len>max_len:
max_len=cur_len
max_index=i
final_tem.append(nest_list[max_index])
return final_tem
def generate_seq_input(nonest_input,outfile):
fin=io.StringIO(nonest_input)
fout=open(outfile,'w',encoding='utf-8')
all_in=fin.read().strip().split('\n\n')
fin.close()
final_input=[]
for doc in all_in:
lines=doc.split('\n')
token_text=lines[0]
pmid=lines[1].split('\t')[0]
# print(pmid)
#read entity and relation
entity_arg1={} #only entity offset
entity_arg2={} #only entity offset
entity_all=[] #all entity infor
for i in range(1,len(lines)):
seg=lines[i].split('\t')
if seg[4]==REL_ENT['arg1']:
if seg[-1] in entity_arg1.keys():
entity_arg1[seg[-1]].append([seg[1],seg[2]])
else:
entity_arg1[seg[-1]]=[[seg[1],seg[2]]]
elif seg[4]==REL_ENT['arg2']:
temp_spes=seg[-1].split(',')
for ele in temp_spes:
gene_spe_id=ele
if gene_spe_id in entity_arg2.keys():
entity_arg2[gene_spe_id].append([seg[1],seg[2]])
else:
entity_arg2[gene_spe_id]=[[seg[1],seg[2]]]
entity_all.append(seg)
# print('\narg1:',entity_arg1)
# print('\narg2:',entity_arg2)
# print('\nall entity:',entity_all)
# for all arg1 to produce inst
for cur_ele in entity_arg1.keys():
#1. ner label text
#check cur_ele in relation?
# print(relation_all.keys())
if cur_ele in entity_arg2.keys(): #pos instance
rel_ent2=entity_arg2[cur_ele]
ner_text=''
text_sid=0
#print('nonest:',entity_nonest)
for ele_nonest in entity_all:
ent_id=[ele_nonest[1],ele_nonest[2]]
ent_sid=int(ele_nonest[1])
ent_eid=int(ele_nonest[2])
# print('sid,eid:',ent_sid,ent_eid)
ent_text=ele_nonest[3]
ent_type=ele_nonest[4]
if ent_sid>=text_sid:
if ent_id in entity_arg1[cur_ele]:
ner_text+=token_text[text_sid:ent_sid]+' '+ENTITY_TAG['arg1'][0]+' '+ent_text+ ' '+ENTITY_TAG['arg1'][1]+' '
else:
if ent_id in rel_ent2: #arg2 entity
if ent_type!=REL_ENT['arg2']:
pass
# print('arg2 is error! not ',REL_ENT['arg2'], ele_nonest)
ner_text+=token_text[text_sid:ent_sid]+' '+ENTITY_TAG['arg2'][0]+' '+ent_text+ ' '+ENTITY_TAG['arg2'][1]+' '
else:
ner_text+=token_text[text_sid:ent_sid]+' '+ENTITY_TAG[ent_type.lower()][0]+' '+ent_text+ ' '+ENTITY_TAG[ent_type.lower()][1]+' '
text_sid=ent_eid
else:
pass
# print('ner entity error!!!',ele_nonest,text_sid)
ner_text+=token_text[text_sid:]
sen_tokens=ner_text.split()
# print('\nner_text:',ner_text)
#3 produce pos input
temp_input=[]
token_id=0
while token_id <len(sen_tokens):
if sen_tokens[token_id].find(ENTITY_TAG['arg1'][0])>=0:
temp_input.append(ENTITY_TAG['arg1'][0]+'\tO')
token_id+=1
while(sen_tokens[token_id]!=ENTITY_TAG['arg1'][1]):
temp_input.append(sen_tokens[token_id]+'\tO')
token_id+=1
temp_input.append(ENTITY_TAG['arg1'][1]+'\tO')
elif sen_tokens[token_id].find(ENTITY_TAG['arg2'][0])>=0:
temp_input.append(ENTITY_TAG[REL_ENT['arg2'].lower()][0]+'\tARG2')
token_id+=1
while(sen_tokens[token_id]!=ENTITY_TAG['arg2'][1]):
temp_input.append(sen_tokens[token_id]+'\tARG2')
token_id+=1
temp_input.append(ENTITY_TAG[REL_ENT['arg2'].lower()][1]+'\tARG2')
elif sen_tokens[token_id].find(ENTITY_TAG['gene'][0])>=0:
temp_input.append(ENTITY_TAG['gene'][0]+'\tO')
token_id+=1
while(sen_tokens[token_id]!=ENTITY_TAG['gene'][1]):
temp_input.append(sen_tokens[token_id]+'\tO')
token_id+=1
temp_input.append(ENTITY_TAG['gene'][1]+'\tO')
elif sen_tokens[token_id].find(ENTITY_TAG['species'][0])>=0:
temp_input.append(ENTITY_TAG['species'][0]+'\tO')
token_id+=1
while(sen_tokens[token_id]!=ENTITY_TAG['species'][1]):
temp_input.append(sen_tokens[token_id]+'\tO')
token_id+=1
temp_input.append(ENTITY_TAG['species'][1]+'\tO')
else:
if sen_tokens[token_id]=='':
# print('token is none!error!')
pass
else:
temp_input.append(sen_tokens[token_id]+'\tO')
token_id+=1
final_input.append('\n'.join(temp_input))
else: #neg instance
ner_text=''
text_sid=0
#print('nonest:',entity_nonest)
for ele_nonest in entity_all:
ent_id=[ele_nonest[1],ele_nonest[2]]
ent_sid=int(ele_nonest[1])
ent_eid=int(ele_nonest[2])
# print('sid,eid:',ent_sid,ent_eid)
ent_text=ele_nonest[3]
ent_type=ele_nonest[4]
if ent_sid>=text_sid:
if ent_id in entity_arg1[cur_ele]:
ner_text+=token_text[text_sid:ent_sid]+' '+ENTITY_TAG['arg1'][0]+' '+ent_text+ ' '+ENTITY_TAG['arg1'][1]+' '
else:
ner_text+=token_text[text_sid:ent_sid]+' '+ENTITY_TAG[ent_type.lower()][0]+' '+ent_text+ ' '+ENTITY_TAG[ent_type.lower()][1]+' '
text_sid=ent_eid
else:
pass
# print('ner entity error!!!')
ner_text+=token_text[text_sid:]
sen_tokens=ner_text.split()
# print('\nner_text:',ner_text)
# print('ner_Text')
#3 produce NEG input
temp_input=[]
token_id=0
while token_id <len(sen_tokens):
if sen_tokens[token_id].find(ENTITY_TAG['arg1'][0])>=0:
temp_input.append(ENTITY_TAG['arg1'][0]+'\tO')
token_id+=1
while(sen_tokens[token_id]!=ENTITY_TAG['arg1'][1]):
temp_input.append(sen_tokens[token_id]+'\tO')
token_id+=1
temp_input.append(ENTITY_TAG['arg1'][1]+'\tO')
elif sen_tokens[token_id].find(ENTITY_TAG['gene'][0])>=0:
temp_input.append(ENTITY_TAG['gene'][0]+'\tO')
token_id+=1
while(sen_tokens[token_id]!=ENTITY_TAG['gene'][1]):
temp_input.append(sen_tokens[token_id]+'\tO')
token_id+=1
temp_input.append(ENTITY_TAG['gene'][1]+'\tO')
elif sen_tokens[token_id].find(ENTITY_TAG['species'][0])>=0:
temp_input.append(ENTITY_TAG['species'][0]+'\tO')
token_id+=1
while(sen_tokens[token_id]!=ENTITY_TAG['species'][1]):
temp_input.append(sen_tokens[token_id]+'\tO')
token_id+=1
temp_input.append(ENTITY_TAG['species'][1]+'\tO')
else:
if sen_tokens[token_id]=='':
print('token is none!error!')
else:
temp_input.append(sen_tokens[token_id]+'\tO')
token_id+=1
final_input.append('\n'.join(temp_input))
# print(entity_nonest)
# sys.exit()
fout.write('\n\n'.join(final_input))
fout.write('\n')
fout.close()
def check_entity_pos(line,relations):
seg=line.split(' ')
stack_ent=[]
# print(seg)
entity_num={'arg1':0,'arg2':0, 'gene':0,'chemical':0}
temp_arg2=[]
for i in range(0,len(seg)):
if seg[i].find(ENTITY_TAG['gene'][0])>=0:
entity_num['gene']+=1
stack_ent.append(seg[i])
elif seg[i].find(ENTITY_TAG['chemical'][0])>=0:
entity_num['chemical']+=1
stack_ent.append(seg[i])
# print(stack_ent)
elif seg[i].find(ENTITY_TAG['arg1'][0])>=0:
entity_num['arg1']+=1
stack_ent.append(seg[i])
elif seg[i].find(ENTITY_TAG['arg2'][0])>=0:
entity_num['arg2']+=1
temp_arg2.append(seg[i].split('|')[0])
stack_ent.append(seg[i])
elif seg[i].find(ENTITY_TAG['arg1'][1])>=0 or seg[i].find(ENTITY_TAG['arg2'][1])>=0 or seg[i].find(ENTITY_TAG['gene'][1])>=0 or seg[i].find(ENTITY_TAG['chemical'][1])>=0:
stack_ent.pop()
if stack_ent!=[]:
# print('entity no match!',stack_ent)
return(-1,seg,entity_num)
else:
if entity_num['arg1']!=0:
for arg2_id in relations.keys():
if arg2_id not in temp_arg2:
# print('\ntemp_arg2:',temp_arg2)
# print('\narg2_id:',arg2_id)
return(0,seg,entity_num) #some arg2 not in sentence
if entity_num['arg2']!=0 and entity_num['arg1']==0:
return(0,seg,entity_num) #only arg2, but no arg1
return(1,seg,entity_num)
def check_entity_neg(line):
seg=line.split(' ')
stack_ent=[]
# print(seg)
entity_num={'arg1':0,'gene':0,'chemical':0}
for i in range(0,len(seg)):
if seg[i].find(ENTITY_TAG['gene'][0])>=0:
entity_num['gene']+=1
stack_ent.append(seg[i])
elif seg[i].find(ENTITY_TAG['chemical'][0])>=0:
entity_num['chemical']+=1
stack_ent.append(seg[i])
# print(stack_ent)
elif seg[i].find(ENTITY_TAG['arg1'][0])>=0:
entity_num['arg1']+=1
stack_ent.append(seg[i])
elif seg[i].find(ENTITY_TAG['arg1'][1])>=0 or seg[i].find(ENTITY_TAG['gene'][1])>=0 or seg[i].find(ENTITY_TAG['chemical'][1])>=0:
stack_ent.pop()
if stack_ent!=[]:
# print('entity no match!',stack_ent)
return(-1,seg,entity_num)
else:
return(1,seg,entity_num)
def get_one_entity(nest_list,cur_ent,rel_entity2_id):
max_len=0
max_entity=[]
final_entity=[]
for i in range(0, len(nest_list)):
if nest_list[i][1]==cur_ent:#current entity
final_entity=[]
max_entity=nest_list[i]
final_entity.append(nest_list[i])
return(final_entity)
if nest_list[i][1] in rel_entity2_id: #invole rel
final_entity.append(nest_list[i])
continue
length=int(nest_list[i][4])-int(nest_list[i][3])
if max_entity==[]: #first entity
max_len=length
max_entity=nest_list[i]
else:
if length>max_len:
if max_entity[2]==REL_ENT['arg1']:
max_len=length
max_entity=nest_list[i]
else:
if nest_list[i][2]==REL_ENT['arg2'] and max_entity[1] not in rel_entity2_id:
max_len=length
max_entity=nest_list[i]
else:
if nest_list[i][1] in rel_entity2_id:
max_len=length
max_entity=nest_list[i]
elif max_entity[2]==REL_ENT['arg1'] and nest_list[i][2]==REL_ENT['arg2']:
max_len=length
max_entity=nest_list[i]
if final_entity==[]:
final_entity.append(max_entity)
return final_entity
if __name__=='__main__':
infile='../../TrainingSet/No505/SA.Train.txt'
outfile='../../TrainingSet/No505/SA.Train.conll'
#tokenizer
token_input=ssplit_token(infile)
#filter nest entity
nonest_input=corpus_noNest(token_input)
# to conll
generate_seq_input(nonest_input,outfile) |