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evaluate.py
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evaluate.py
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import read_datasets
import random
import time
from SPARQLWrapper import SPARQLWrapper,JSON
def supplementary_sample_dict():
return dict
def sample_wiki_annotated_data():
supplement = True
if supplement==False:
wiki_write_file = open("resource/WD27M_SAMPLED.tsv", "w", encoding="utf-8")
else:
wiki_write_file = open("resource/WD27M_SAMPLED_supplement.tsv", "w", encoding="utf-8")
wikidata_prefix = "wd:"
wd_predicate_file = open("resource/wikidata_predicates_list.tsv", "r", encoding="UTF-8")
wd_predicate_list = {}
wd_predicate_file.readline()
wd_predicates = wd_predicate_file.readlines()
'''compute sampling percentage'''
wiki_facts_num = {}
wiki_sampling = {}
sample_numbers = 10000
for item in wd_predicates:
item = item.strip()
elements = item.split("\t")
# if elements[2]=="True":
# wd_predicate_list.append
predicate = elements[0]
facts = int(elements[3])
isTemporal = elements[2]
wd_predicate_list[predicate] = facts
# 7471929
wiki_temporal_facts = 7471929
if isTemporal == "True":
num = int(facts * 1.0 * sample_numbers / wiki_temporal_facts)
if num == 0:
num = 1
wiki_sampling[predicate] = num
wiki_facts_num[predicate] = facts
for item in wiki_sampling.keys():
print(item.replace("wd:","")+"\t"+str(wiki_sampling[item]))
# print(wiki_sampling)
print(sum(wiki_sampling.values()))
'''supplement'''
if supplement==True:
dict = {}
file = "resource/wiki_sup.txt"
with open(file, "r", encoding="utf-8") as file:
lines = file.readlines()
max_sup_number = 10000
for line in lines:
p = "wd:" + line.split("\t")[0]
# print(p)
# if wiki_facts_num[p]<max_sup_number:
# dict[p]=wiki_facts_num[p]
# else:
# dict[p] = max_sup_number
# print(wiki_facts_num[p])
dict[p]=int(line.strip().split("\t")[1])
wiki_sampling=dict
# print(wiki_sampling)
'''smapling'''
wiki_sampling_index = {}
for key in wiki_sampling:
wiki_sampling_index[key] = random.sample(range(0, wiki_facts_num[key]), wiki_sampling[key])
# print(wiki_sampling_index)
WIKIDATA = "resource/WD27M.tsv"
utkg_wiki = read_datasets.read_file(WIKIDATA)
# print(utkg_wiki[0])
# ['Q27067701', 'P735', 'Q3133296', 'null', 'null']
wiki_sampling_pointer = {}
for key in wiki_sampling:
wiki_sampling_pointer[key]=-1
wiki_sampled_dataset = []
for quad in utkg_wiki:
predicate=wikidata_prefix+quad[1]
if predicate in wiki_sampling:
wiki_sampling_pointer[predicate]+=1
if wiki_sampling_pointer[predicate] in wiki_sampling_index[predicate]:
wiki_sampled_dataset.append(quad)
# print(sum(wd_predicate_list.values()))
for quad in wiki_sampled_dataset:
line = quad[0] + "\t" + quad[1] + "\t" + quad[2] + "\t" + quad[3] + "\t" + quad[4] + "\n"
wiki_write_file.write(line)
def sample_free_annotated_data():
freebase_prefix = "fb:"
free_facts_num = {}
fb_predicate_file = open("resource/freebase_predicates_list.tsv", "r", encoding="UTF-8")
fb_predicate_list = {}
free_sampling = {}
fb_predicate_file.readline()
fb_predicates = fb_predicate_file.readlines()
sample_numbers = 128
for item in fb_predicates:
item = item.strip()
elements = item.split("\t")
# if elements[2]=="True":
# wd_predicate_list.append
predicate = elements[0]
facts = int(elements[3])
isTemporal = elements[2]
fb_predicate_list[predicate] = facts
# 2989799
free_temporal_facts = 2989799
if isTemporal == "True":
num = int(facts * 1.0 * sample_numbers / free_temporal_facts)
num += 1
free_sampling[predicate] = num
free_facts_num[predicate] = facts
print(free_sampling)
print(sum(free_sampling.values()))
# List=random.sample(range(0,10),10)
# print(List)
free_sampling_index = {}
for key in free_sampling:
free_sampling_index[key] = random.sample(range(0, free_facts_num[key]), free_sampling[key])
# print(free_sampling_index)
FREEBASE = "resource/FB37M.tsv"
free_sampling_pointer = {}
'''initiate pointer'''
for key in free_sampling:
free_sampling_pointer[key] = -1
free_sampled_dataset = []
utkg_free = read_datasets.read_file(FREEBASE)
for quad in utkg_free:
predicate = freebase_prefix + quad[1]
if predicate in free_sampling:
free_sampling_pointer[predicate] += 1
if free_sampling_pointer[predicate] in free_sampling_index[predicate]:
free_sampled_dataset.append(quad)
# else:
# print(predicate)
# print(sum(fb_predicate_list.values()))
free_write_file = open("resource/FB37M_SAMPLED.tsv", "w", encoding="utf-8")
for quad in free_sampled_dataset:
line = quad[0] + "\t" + quad[1] + "\t" + quad[2] + "\t" + quad[3] + "\t" + quad[4] + "\n"
free_write_file.write(line)
def sample_annotated_data():
sample_wiki_annotated_data()
# sample_free_annotated_data()
# wikidata_prefix = "wd:"
# wd_predicate_file = open("resource/wikidata_predicates_list.tsv", "r", encoding="UTF-8")
# wd_predicate_list = {}
# wd_predicate_file.readline()
# wd_predicates = wd_predicate_file.readlines()
# filename="resource/.tsv"
# utkg=read_file(filename)
# print(wd_predicates)
'''initiate dictionary'''
# for item in wd_predicates:
# item=item.strip()
# elements=item.split("\t")
# # if elements[2]=="True":
# # wd_predicate_list.append
# predicate=elements[0]
# wd_predicate_list[predicate]=0
# fb_predicate_file.readline()
# fb_predicates=fb_predicate_file.readlines()
# for item in fb_predicates:
# item=item.strip()
# elements=item.split("\t")
# # if elements[2]=="True":
# # wd_predicate_list.append
# predicate=elements[0]
# fb_predicate_list[predicate]=0
# print(wd_predicate_list)
# print(fb_predicate_list)
# print(len(wd_predicate_list))
# print(len(fb_predicate_list))
'''count facts'''
# WIKIDATA = "resource/WD27M.tsv"
# FREEBASE = "resource/FB37M.tsv"
#
# utkg_wiki=read_file(WIKIDATA)
# # print(utkg_wiki[0])
# # ['Q27067701', 'P735', 'Q3133296', 'null', 'null']
# for quad in utkg_wiki:
# predicate=wikidata_prefix+quad[1]
# wd_predicate_list[predicate]+=1
# # print(sum(wd_predicate_list.values()))
#
# utkg_free=read_file(FREEBASE)
# for quad in utkg_free:
# predicate=freebase_prefix+quad[1]
# if predicate in fb_predicate_list:
# fb_predicate_list[predicate]+=1
# else:
# print(predicate)
# print(sum(fb_predicate_list.values()))
# KeyError: 'http://www.w3.org/2000/01/rdf-schema#range'
# KeyError: 'http://www.w3.org/2000/01/rdf-schema#domain'
# wd_predicate_file.close()
# fb_predicate_file.close()
'''rewrite file'''
# write_wiki_predicates=open("resource/wikidata_predicates_list.tsv","w",encoding="UTF-8")
# write_free_predicates=open("resource/freebase_predicates_list.tsv","w",encoding="UTF-8")
# write_wiki_predicates.write("predicate"+"\t"+"label"+"\t"+"?temporal_predicate"+"\t"+"facts"+"\n")
# write_free_predicates.write("predicate" + "\t" + "label" + "\t" + "?temporal_predicate" + "\t" + "facts" + "\n")
# for item in wd_predicates:
# item=item.strip()
# elements=item.split("\t")
# # if elements[2]=="True":
# # wd_predicate_list.append
# predicate=elements[0]
# item=item+"\t"+str(wd_predicate_list[predicate])+"\n"
# write_wiki_predicates.write(item)
#
# for item in fb_predicates:
# item=item.strip()
# elements=item.split("\t")
# # if elements[2]=="True":
# # wd_predicate_list.append
# predicate=elements[0]
# item=item+"\t"+str(fb_predicate_list[predicate])+"\n"
# write_free_predicates.write(item)
def query_wikidata():
'''
human(Q5)
sports team (Q12973014)
human-geographic territorial entity (Q15642541)
human settlement (Q486972)
'''
# Set up the SPARQL endpoint URL
sparql = SPARQLWrapper("https://query.wikidata.org/sparql")
# Define the Wikidata query to retrieve information about Albert Einstein
query = """
SELECT ?property ?value WHERE {
wd:Q937 ?property ?value .
SERVICE wikibase:label { bd:serviceParam wikibase:language "en" }
}
""".format()
# Set the query and return format
sparql.setQuery(query)
sparql.setReturnFormat(JSON)
# Execute the query and parse the results
results = sparql.query().convert()
# Print the results
for result in results["results"]["bindings"]:
print(result["property"]["value"], result["value"]["value"])
def reformat_time(t):
#YYYYY/MM/DD
#"2013-01-31T00:00:00Z"^^xsd:dateTime
#"-0220-01-01T00:00:00Z"^^xsd:dateTime
DD=t.__getitem__(len(t)-2)+t.__getitem__(len(t)-1)
MM=t.__getitem__(len(t)-4)+t.__getitem__(len(t)-3)
YY=t[0:len(t)-4]
DATE=YY+"-"+MM+"-"+DD
# print(DATE)
dateTime="\""+DATE+"T00:00:00Z\"^^xsd:dateTime"
# print(dateTime)
return dateTime
def select_mutiple_wiki():
# incomplete
wiki_file="resource/wiki_annotated_file.tsv"
mutiple_values=[]
with open(wiki_file,"r",encoding="utf-8") as file:
lines= file.readlines()
for line in lines:
ele = line.split("\t")
label =ele[0]
if label=="-1":
mutiple_values.append(ele)
sparql = SPARQLWrapper("https://query.wikidata.org/sparql")
for fact in mutiple_values:
s = fact[1]
p = fact[2]
o = fact[3]
start = fact[4]
# end = fact[4]
year=o.split("-")[0]
def truth_verification_wiki():
supplement=False
if supplement==False:
wiki_to_verify = "resource/WD27M_SAMPLED.tsv"
wiki_annotated_file = open("resource/wiki_annotated_file.tsv", "a", encoding="utf-8")
else:
wiki_to_verify = "resource/WD27M_SAMPLED_supplement.tsv"
wiki_annotated_file = open("resource/wiki_supplement_annotated_file.tsv", "a", encoding="utf-8")
# p580 start time
# p582 end time
# p585 point in time
wiki_file = open(wiki_to_verify, "r", encoding="utf-8")
delay_time = 1
temporal_binding = open("resource/wikidata_temporal_property_type.tsv", "r", encoding="utf-8")
temporal_binding.readline()
temporal_types = temporal_binding.readlines()
temporal_binding_dict = {}
for item in temporal_types:
item = item.strip()
item_s = item.split("\t")
predicate = item_s[0]
temporal_type = item_s[1]
temporal_binding_dict[predicate] = temporal_type
# period point
temporal_binding_dict["P569"] = "point"
temporal_binding_dict["P570"] = "point"
wiki_lines = wiki_file.readlines()
# # TEST 1
# s = "Q10520"
# p = "P54"
# o = "Q483020"
# # o maybe str
# start=""2013-01-31T00:00:00Z"^^xsd:dateTime"
# end=""2013-05-17T00:00:00Z"^^xsd:dateTime"
# wiki_annotated_file.write("label\ts\tp\to\tst\ted\n")
sparql = SPARQLWrapper("https://query.wikidata.org/sparql")
# if old version consistent to the current one
count = 0
for line in wiki_lines:
# count+=1
# if count==2:
# break
line = line.strip()
fact = line.split("\t")
s = fact[0]
p = fact[1]
o = fact[2]
start = fact[3]
end = fact[4]
temporal_type = temporal_binding_dict[p]
# switch case
if p.__eq__("P569") or p.__eq__("P570"):
start_time = reformat_time(start)
query = """SELECT ?s WHERE {{wd:{} wdt:{} ?s.}}""".format(s, p)
elif o[0] != "Q":
if start.__eq__("null") and end.__eq__("null"):
continue
elif start.__eq__("null"):
end_time = reformat_time(end)
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s pq:P582 {}.
}}
""".format(s, p, end_time)
elif end.__eq__("null"):
start_time = reformat_time(start)
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s pq:P580 {}.
}}
""".format(s, p, start_time)
else:
start_time = reformat_time(start)
end_time = reformat_time(end)
if temporal_type == "period":
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s pq:P580 {}.
?s pq:P582 {}.
}}
""".format(s, p, start_time, end_time)
else:
# temporal type = point
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s pq:P585 {}.
}}
""".format(s, p, start_time)
else:
if start.__eq__("null") and end.__eq__("null"):
continue
elif start.__eq__("null"):
end_time = reformat_time(end)
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s ps:{} wd:{}.
?s pq:P582 {}.
}}
""".format(s, p, p, o, end_time)
elif end.__eq__("null"):
start_time = reformat_time(start)
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s ps:{} wd:{}.
?s pq:P580 {}.
}}
""".format(s, p, p, o, start_time)
else:
start_time = reformat_time(start)
end_time = reformat_time(end)
if temporal_type == "period":
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s ps:{} wd:{}.
?s pq:P580 {}.
?s pq:P582 {}.
}}
""".format(s, p, p, o, start_time, end_time)
else:
# temporal type = point
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s ps:{} wd:{}.
?s pq:P585 {}.
}}
""".format(s, p, p, o, start_time)
sparql.setQuery(query)
sparql.setReturnFormat(JSON)
# 执行查询并检查结果是否存在
try:
results = sparql.query().convert()
except Exception as e:
print(e)
print("retrying......")
time.sleep(60)
results = sparql.query().convert()
if len(results["results"]["bindings"]) > 0:
if p.__eq__("P569") or p.__eq__("P570"):
start_time = reformat_time(start)
DATE = start_time.split("\"")[1]
exist = 0
for result in results["results"]["bindings"]:
# print(result["s"]["value"])
# print(start_time)
if result["s"]["value"] == DATE:
exist = 1
if exist == 1:
if len(results["results"]["bindings"]) > 1:
line = "-1\t" + line + "\n"
else:
line = "1\t" + line + "\n"
else:
line = "0\t" + line + "\n"
else:
line = "1\t" + line + "\n"
# return True
else:
line = "0\t" + line + "\n"
# return False
wiki_annotated_file.write(line)
time.sleep(delay_time)
def truth_verification_free():
# freebase
# date_of_birth P569
# date_of_death P570
# teams P54
# spouse_s P26
# employment_history P108
# coaches P286
# free_to_verify = "resource/selected_fb_facts.tsv"
free_to_verify= "resource/FB37M_SAMPLED.tsv"
# free_to_verify = "resource/temp.txt"
free_file=open(free_to_verify,"r",encoding="utf-8")
free_lines = free_file.readlines()
delay_time = 1
relation_map={}
relation_map["people.deceased_person.date_of_death"]="P570"
relation_map["people.person.date_of_birth"]="P569"
relation_map["sports.pro_athlete.teams"] = "P54"
relation_map["people.person.spouse_s"] = "P26"
relation_map["people.person.employment_history"] = "P108"
relation_map["sports.sports_team.coaches"] = "P286"
temporal_binding_dict = {}
temporal_binding_dict["P569"] = "point"
temporal_binding_dict["P570"] = "point"
temporal_binding_dict["P54"] = "period"
temporal_binding_dict["P26"] = "period"
temporal_binding_dict["P108"] = "period"
temporal_binding_dict["P286"] = "period"
# # TEST 1
# s = "Q10520"
# p = "P54"
# o = "Q483020"
# # o maybe str
# start=""2013-01-31T00:00:00Z"^^xsd:dateTime"
# end=""2013-05-17T00:00:00Z"^^xsd:dateTime"
id_maps={}
with open("resource/FBids_to_WDids.tsv","r",encoding="utf-8") as id_maps_file:
lines=id_maps_file.readlines()
for pair in lines:
pair=pair.strip()
fbid=pair.split("\t")[0]
wdid=pair.split("\t")[1]
id_maps[fbid]=wdid
free_annotated_file = open("resource/temp_free_annotated_file.tsv", "a", encoding="utf-8")
# free_annotated_file.write("label\ts\tp\to\tst\ted\n")
sparql = SPARQLWrapper("https://query.wikidata.org/sparql")
# if old version consistent to the current one
count = 0
for line in free_lines:
# count+=1
# if count==10:
# break
line = line.strip()
fact = line.split("\t")
if fact[0] in id_maps:
s=id_maps[fact[0]]
else:
continue
#relation map
p = relation_map[fact[1]]
if p!="P569" and p!="P570":
if fact[2] in id_maps:
o=id_maps[fact[2]]
else:
continue
start = fact[3]
end = fact[4]
temporal_type = temporal_binding_dict[p]
# switch case
if p.__eq__("P569") or p.__eq__("P570"):
start_time = reformat_time(start)
query = """SELECT ?s WHERE {{wd:{} wdt:{} ?s.}}""".format(s, p)
else:
if start.__eq__("null") and end.__eq__("null"):
continue
elif start.__eq__("null"):
end_time = reformat_time(end)
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s ps:{} wd:{}.
?s pq:P582 {}.
}}
""".format(s, p, p, o, end_time)
elif end.__eq__("null"):
start_time = reformat_time(start)
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s ps:{} wd:{}.
?s pq:P580 {}.
}}
""".format(s, p, p, o, start_time)
else:
start_time = reformat_time(start)
end_time = reformat_time(end)
if temporal_type == "period":
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s ps:{} wd:{}.
?s pq:P580 {}.
?s pq:P582 {}.
}}
""".format(s, p, p, o, start_time, end_time)
else:
# temporal type = point
query = """
SELECT ?s
WHERE {{
wd:{} p:{} ?s.
?s ps:{} wd:{}.
?s pq:P585 {}.
}}
""".format(s, p, p, o, start_time)
sparql.setQuery(query)
sparql.setReturnFormat(JSON)
# 执行查询并检查结果是否存在
try:
results = sparql.query().convert()
except Exception as e:
print(e)
print("retrying......")
time.sleep(60)
results = sparql.query().convert()
if len(results["results"]["bindings"]) > 0:
if p.__eq__("P569") or p.__eq__("P570"):
start_time = reformat_time(start)
DATE = start_time.split("\"")[1]
exist = 0
for result in results["results"]["bindings"]:
# print(result["s"]["value"])
# print(start_time)
if result["s"]["value"] == DATE:
exist = 1
if exist == 1:
if len(results["results"]["bindings"]) > 1:
line = "-1\t" + line + "\n"
else:
line = "1\t" + line + "\n"
else:
line = "0\t" + line + "\n"
else:
line = "1\t" + line + "\n"
# return True
else:
line = "0\t" + line + "\n"
# return False
free_annotated_file.write(line)
time.sleep(delay_time)
def truth_verification():
truth_verification_wiki()
# truth_verification_free()
def deduplicate_annotated_files():
filename="resource/wiki_annotated_file.tsv"
filename="resource/wiki_right.txt"
with open(filename, "r", encoding="utf-8") as file:
# file.readline()
unique_lines = set(file.readlines())
# Write the unique lines to a new file
new_filename="resource/unique_wiki_a.tsv"
with open(new_filename, "w",encoding="utf-8") as unique_file:
# unique_file.write("label\ts\tp\to\tst\ted\n")
unique_file.writelines(unique_lines)
def fbid_to_wdid():
# Replace with the Freebase ID you want to query
fb_ids=open("resource/entities_to_map.tsv","r",encoding="utf-8")
lines = fb_ids.readlines()
sparql = SPARQLWrapper("http://114.212.81.217:8890/sparql/")
# id_map={}
map_files=open("resource/FBids_to_WDids.tsv","a",encoding="utf-8")
count=0
for freebase_id in lines:
# count+=1
# if count==20:
# break
freebase_id=freebase_id.strip()
new_freebase_id="/"+freebase_id.replace(".","/")
# print(freebase_id)
# Construct the SPARQL query
query = """
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?item WHERE {{
?item wdt:P646 "{}".
}}
""".format(new_freebase_id)
# Send the SPARQL query to the Wikidata API
sparql.setQuery(query)
sparql.setReturnFormat(JSON)
response = sparql.query().convert()
# Parse the response and extract the entity information
if len(response["results"]["bindings"])>0:
item_id = response["results"]["bindings"][0]["item"]["value"]
# print(item_id)
map_files.write(freebase_id+"\t"+item_id.replace("http://www.wikidata.org/entity/","")+"\n")
map_files.close()
def entity_in_temporal_fact():
utkg=read_datasets.read_file("resource/FB37M.tsv")
temporal_entity=set()
for fact in utkg:
if fact[3]!="null" or fact[4]!="null":
if fact.__contains__("m."):
temporal_entity.add(fact[0])
if fact[2].__contains__("m."):
temporal_entity.add(fact[2])
has_mapped_entitiy=set()
with open("resource/FBids_to_WDids.tsv","r",encoding="utf-8") as file:
lines=file.readlines()
for line in lines:
line=line.strip()
id=line.split("\t")[0]
has_mapped_entitiy.add(id)
difference=temporal_entity-has_mapped_entitiy
with open("resource/entities_to_map.tsv","w",encoding="utf-8") as file1:
for i in difference:
file1.write(i+"\n")
def auto_evaluate_wiki():
# wiki_dict={}
std_confidence=False
if std_confidence==True:
conflict_file = "Std_results/Conflicts in WD27M.txt"
else:
conflict_file = "output/WD27M.all_conflicts"
wiki_annotated_set = set()
wiki_wrong="resource/WD27M_wrong_facts.tsv"
with open(wiki_wrong, "r", encoding="utf-8") as wikitest:
wikitest.readline()
test_lines = wikitest.readlines()
for line in test_lines:
line = line.strip()
# print(line)
ele = line.split("\t")
fact = ele[1] + "," + ele[2] + "," + ele[3] + "," + ele[4] + "," + ele[5]
if ele[0] == "-1" or ele[0] == "0":
# wiki_dict[fact]=ele[0]
wiki_annotated_set.add(fact)
# print(wiki_annotated_set)
detected_set = set()
temporal_represenation_file="output/WD27M.temporal_representation_conflicts"
with open(temporal_represenation_file,"r",encoding="utf-8") as tr:
conflict_lines=tr.readlines()
for line in conflict_lines:
line=line.strip()
detected_set.add(line)
with open(conflict_file, "r", encoding="utf-8") as wdconflict:
conflict_lines = wdconflict.readlines()
for line in conflict_lines:
line = line.strip()
ele = line.split("\t")
fact1 = ele[1]
fact2 = ele[2]
fact_ele = fact1.split(",")
if len(fact_ele) == 7:
# if len(fact_ele[3].split("*"))!=1:
fact_ele[3]=fact_ele[3].split("*")[0]
fact1 = fact_ele[2] + "," + fact_ele[3] + "," + fact_ele[4] + "," + fact_ele[5] + "," + fact_ele[6]
else:
fact_ele[1] = fact_ele[1].split("*")[0]
fact1 = fact_ele[0] + "," + fact_ele[1] + "," + fact_ele[2] + "," + fact_ele[3] + "," + fact_ele[4]
fact_ele = fact2.split(",")
if len(fact_ele) == 7:
# if len(fact_ele[3].split("*"))!=1:
fact_ele[3] = fact_ele[3].split("*")[0]
fact2 = fact_ele[2] + "," + fact_ele[3] + "," + fact_ele[4] + "," + fact_ele[5] + "," + fact_ele[6]
else:
fact_ele[1] = fact_ele[1].split("*")[0]
fact2 = fact_ele[0] + "," + fact_ele[1] + "," + fact_ele[2] + "," + fact_ele[3] + "," + fact_ele[4]
detected_set.add(fact1)
detected_set.add(fact2)
# print(detected_set)
# for item in detected_set:
# if item.__contains__("*"):
# print("yes")
covered_set = detected_set.intersection(wiki_annotated_set)
recall = len(covered_set) * 1.0 / len(wiki_annotated_set)
print(len(wiki_annotated_set))
print(recall)
def auto_evaluate_wiki_aaai17():
# wiki_dict={}
wiki_annotated_set = set()
wiki_wrong = "resource/WD27M_wrong_facts.tsv"
with open(wiki_wrong, "r", encoding="utf-8") as wikitest:
wikitest.readline()
test_lines = wikitest.readlines()
for line in test_lines:
line = line.strip()
# print(line)
ele = line.split("\t")
if ele[4]=="-1":
ele[4]=ele[5]
if ele[5]=="-1":
ele[5]=ele[4]
ele[4] = ele[4][0:4]
ele[5] = ele[5][0:4]
fact = ele[1] + "," + ele[2] + "," + ele[3] + "," + ele[4] + "," + ele[5]
if ele[0] == "-1" or ele[0] == "0":
# wiki_dict[fact]=ele[0]
wiki_annotated_set.add(fact)
# print(wiki_annotated_set)
conflict_file = "tecore/WDconflict_web.cons"
detected_set=set()
with open(conflict_file, "r", encoding="utf-8") as wdconflict:
conflict_lines = wdconflict.readlines()
for line in conflict_lines:
line = line.strip()
ele = line.split("\t")
fact = ele[0] + "," + ele[1] + "," + ele[2] + "," + ele[3] + "," + ele[4]
detected_set.add(fact)
covered_set = detected_set.intersection(wiki_annotated_set)
# for item in covered_set:
# print(item)
# print(covered_set)
recall = len(covered_set) * 1.0 / len(wiki_annotated_set)
print(len(wiki_annotated_set))
print(recall)
def auto_evaluate_free():
# free_dict={}
free_annotated_set = set()
detected_set = set()
wrong_file="resource/FB37M_wrong_facts.tsv"
with open(wrong_file, "r", encoding="utf-8") as freetest:
freetest.readline()
test_lines = freetest.readlines()
for line in test_lines:
line = line.strip()
ele = line.split("\t")
# if ele[3][0:2]!="m.":
# # print(ele[3])
# ele[3]="T"
fact = ele[1] + "," + ele[2] + "," + ele[3] + "," + ele[4] + "," + ele[5]
# free_dict[fact]=ele[0]
if ele[0] == "-1" or ele[0] == "0":
# wiki_dict[fact]=ele[0]
free_annotated_set.add(fact)
# print(free_annotated_set)
detected_set = set()
temporal_represenation_file="output/FB37M.temporal_representation_conflicts"
with open(temporal_represenation_file,"r",encoding="utf-8") as tr:
conflict_lines=tr.readlines()
for line in conflict_lines:
line=line.strip()
detected_set.add(line)
conflict_file="output/FB37M.all_conflicts"
# conflict_file = "Std_results/Conflicts in FB37M.txt"
with open(conflict_file, "r", encoding="utf-8") as fbconflict:
conflict_lines = fbconflict.readlines()
for line in conflict_lines:
line = line.strip()
ele = line.split("\t")
fact1 = ele[1]
fact2 = ele[2]
fact_ele = fact1.split(",")
if len(fact_ele) == 7:
fact1 = fact_ele[2] + "," + fact_ele[3] + "," + fact_ele[4] + "," + fact_ele[5] + "," + fact_ele[6]
else:
fact1=fact_ele[0] + "," + fact_ele[1] + "," + fact_ele[2] + "," + fact_ele[3] + "," + fact_ele[4]
fact_ele = fact2.split(",")
if len(fact_ele) == 7:
fact2 = fact_ele[2] + "," + fact_ele[3] + "," + fact_ele[4] + "," + fact_ele[5] + "," + fact_ele[6]
else:
fact2 = fact_ele[0] + "," + fact_ele[1] + "," + fact_ele[2] + "," + fact_ele[3] + "," + fact_ele[4]
detected_set.add(fact1)
detected_set.add(fact2)
# print(detected_set)
covered_set = detected_set.intersection(free_annotated_set)
print(len(covered_set))
for item in covered_set:
print(item)
recall = len(covered_set) * 1.0 / len(free_annotated_set)
print(len(free_annotated_set))
print(recall)
def auto_evaluate_free_aaai17():
# free_dict={}
free_annotated_set = set()
detected_set = set()
wrong_file = "resource/FB37M_wrong_facts.tsv"
with open(wrong_file, "r", encoding="utf-8") as freetest:
freetest.readline()
test_lines = freetest.readlines()
for line in test_lines:
line = line.strip()
ele = line.split("\t")
# special process
if ele[4]=="-1":
ele[4]=ele[5]
if ele[5]=="-1":
ele[5]=ele[4]
ele[4]=ele[4][0:4]
ele[5] = ele[5][0:4]
fact = ele[1] + "," + ele[2] + "," + ele[3] + "," + ele[4] + "," + ele[5]
# free_dict[fact]=ele[0]
if ele[0] == "-1" or ele[0] == "0":
# wiki_dict[fact]=ele[0]
free_annotated_set.add(fact)
# print(free_annotated_set)
relation_map={}
relation_map["P570"] = "people.deceased_person.date_of_death"
relation_map["P569"] = "people.person.date_of_birth"
relation_map["P54"] = "sports.pro_athlete.teams"
relation_map["P26"] = "people.person.spouse_s"
relation_map["P108"] = "people.person.employment_history"
relation_map["P286"] = "sports.sports_team.coaches"
conflict_file = "tecore/FBconflict_web.cons"
with open(conflict_file, "r", encoding="utf-8") as fbconflict:
conflict_lines = fbconflict.readlines()
for line in conflict_lines:
line = line.strip()
ele = line.split("\t")
ele[1]=relation_map[ele[1]]
fact=ele[0]+ "," + ele[1] + "," + ele[2] + "," + ele[3] + "," + ele[4]
detected_set.add(fact)
# print(detected_set)
covered_set = detected_set.intersection(free_annotated_set)
for item in covered_set:
print(item)
# print(covered_set)
recall = len(covered_set) * 1.0 / len(free_annotated_set)
print(len(free_annotated_set))
print(recall)
def automatic_evaluate():
# 411
# 0.5790754257907542
# 411
# 0.23114355231143552
auto_evaluate_wiki()
auto_evaluate_wiki_aaai17()
# 128
# 0.1953125
# 128
# 0.0859375
auto_evaluate_free()
auto_evaluate_free_aaai17()
def select_all_mapped_facts():
ids_map={}
with open("resource/FBids_to_WDids.tsv","r",encoding="utf-8") as file:
lines=file.readlines()
for line in lines:
line = line.strip()
ele=line.split("\t")
ids_map[ele[0]]=ele[1]
free_utkg=read_datasets.read_file("resource/FB37M.tsv")
selected_facts=[]
for fact in free_utkg:
s=fact[0]
o=fact[2]
st=fact[3]
ed=fact[4]
if st!="null" or ed!="null":
if s in ids_map:
if o[1]==".":
if o in ids_map:
str_fact=fact[0]+"\t"+fact[1]+"\t"+fact[2]+"\t"+fact[3]+"\t"+fact[4]
selected_facts.append(str_fact)
else:
str_fact = fact[0] + "\t" + fact[1] + "\t" + fact[2] + "\t" + fact[3] + "\t" + fact[4]
selected_facts.append(str_fact)
with open("resource/selected_fb_facts.tsv","w",encoding="utf-8") as file1:
file1.write("\n".join(selected_facts))
def tranlate():
relation_map = {}