-
Notifications
You must be signed in to change notification settings - Fork 11
/
create_neighbor.py
executable file
·151 lines (106 loc) · 4.61 KB
/
create_neighbor.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
from collections import defaultdict
import time
import argparse
id2entity_name = defaultdict(str)
parser = argparse.ArgumentParser()
parser.add_argument("--dataset", type=str, default=None)
args = parser.parse_args()
# dataset_name = 'FB15k-237'
with open('./' + args.dataset + '/get_neighbor/entity2id.txt', 'r') as file:
entity_lines = file.readlines()
for line in entity_lines:
_name, _id = line.strip().split("\t")
id2entity_name[int(_id)] = _name
id2relation_name = defaultdict(str)
with open('./' + args.dataset + '/get_neighbor/relation2id.txt', 'r') as file:
relation_lines = file.readlines()
for line in relation_lines:
_name, _id = line.strip().split("\t")
id2relation_name[int(_id)] = _name
train_triplet = []
for line in open('./' + args.dataset + '/get_neighbor/train2id.txt', 'r'):
head, relation, tail = line.strip('\n').split()
train_triplet.append(list((int(head), int(relation), int(tail))))
for line in open('./' + args.dataset + '/get_neighbor/test2id.txt', 'r'):
head, relation, tail = line.strip('\n').split()
train_triplet.append(list((int(head), int(relation), int(tail))))
for line in open('./'+args.dataset+'/get_neighbor/valid2id.txt', 'r'):
head, relation, tail = line.strip('\n').split()
train_triplet.append(list((int(head), int(relation), int(tail))))
graph = {}
reverse_graph = {}
def init_graph(graph_triplet):
for triple in graph_triplet:
head = triple[0]
rela = triple[1]
tail = triple[2]
if(head not in graph.keys()):
graph[head] = {}
graph[head][tail] = rela
else:
graph[head][tail] = rela
if(tail not in reverse_graph.keys()):
reverse_graph[tail] = {}
reverse_graph[tail][head] = rela
else:
reverse_graph[tail][head] = rela
# return graph, reverse_graph, node_indegree, node_outdegree
init_graph(train_triplet)
import random
def random_delete(triplet, reserved_num):
reserved = random.sample(triplet, reserved_num)
return reserved
def get_onestep_neighbors(graph, source, sample_num):
triplet = []
try:
nei = list(graph[source].keys())
# nei = random.sample(graph[source].keys(), sample_num)
triplet = [tuple((source, graph[source][nei[i]], nei[i])) for i in range(len(nei))]
except KeyError:
pass
except ValueError:
nei = list(graph[source].keys())
triplet = [tuple((source, graph[source][nei[i]], nei[i])) for i in range(len(nei))]
return triplet
def get_entity_neighbors(traget_entity, max_triplet):
as_head_neighbors = get_onestep_neighbors(graph, traget_entity, max_triplet // 2)
as_tail_neighbors = get_onestep_neighbors(reverse_graph, traget_entity, max_triplet // 2)
all_triplet = as_head_neighbors + as_tail_neighbors
return all_triplet
def get_triplet(triplet):
head_entity = triplet[0]
tail_entity = triplet[2]
triplet = tuple((triplet[0], triplet[1], triplet[2]))
head_triplet = get_entity_neighbors(head_entity, 4)
tail_triplet = get_entity_neighbors(tail_entity, 4)
temp_triplet = list(set(head_triplet + tail_triplet))
temp_triplet = list(set(temp_triplet) - set([triplet]))
# if len(temp_triplet) > 8:
# del_triplet = list(set(temp_triplet) - set([triplet]))
# temp_triplet = random_delete(del_triplet, 7)
return temp_triplet
import copy
def change_(triplet_list):
tri_text = []
for item in triplet_list:
# text = id2entity_name[item[0]] + '\t' + id2relation_name[item[1]] + '\t' + id2entity_name[item[2]]
h = id2entity_name[item[0]]
r = id2relation_name[item[1]]
t = id2entity_name[item[2]]
tri_text.append([h, r, t])
return tri_text
mask_idx = 99999999
masked_tail_neighbor = defaultdict(list)
masked_head_neighbor = defaultdict(list)
for triplet in train_triplet:
tail_masked = copy.deepcopy(triplet)
head_masked = copy.deepcopy(triplet)
tail_masked[2] = mask_idx
head_masked[0] = mask_idx
masked_tail_neighbor['\t'.join([id2entity_name[triplet[0]], id2relation_name[triplet[1]]])] = change_(get_triplet(tail_masked))
masked_head_neighbor['\t'.join([id2entity_name[triplet[2]], id2relation_name[triplet[1]]])] = change_(get_triplet(head_masked))
import json
with open("./" + args.dataset + "/masked_tail_neighbor.txt", "w") as file:
file.write(json.dumps(masked_tail_neighbor, indent=1))
with open("./" + args.dataset + "/masked_head_neighbor.txt", "w") as file:
file.write(json.dumps(masked_head_neighbor, indent=1))