intrduction

This is a combined framework integrating embedding method and rule-based reasonging to implement better link prediction.

operating method

1. Before running the reasoning, you must prepare the data well. There are some simple constraints about the data to be used.

   1. A raw data set should consist of six files, w.r.t entity2id, relation2id, train, test, rule and a valid set is not a must.

   2. The rule file contains the rules that are essential in reasoning. We get these rules throw some open work, here we use amie. The format of a rule is like:

      ?f /film/director/film ?a ?b /influence/influence_node/peers./influence/peer_relationship/peers ?f => ?a /film/film/edited_by ?b 1

      rule.txt is not the source file of an official data set, we shoule use amie algorithm to generate them with: java -jar amie_plus.jar test.txt > ans.txt. Before running amie_plus.jar, the data in test.txt should meet the form of tsv and each line a triplet of (h,r,t), where h and t are both entities and r is a relation.

2. Reasoning will be operate by means of embedding model to get the embedding of entities and relations. The work of thu can be used https://github.com/thunlp/Fast-TransX . Three examples have been existing in the folders of transE, transH and transR respectively. These examples are about FB15k data set.

3. After the first two steps, some other pre-parations follow. And these codes are contained in preprocess.py.

   • pyhon preprocess.py 1 simplify_rules
   • pyhon preprocess.py 2 construct_knowledge_base
   • pyhon preprocess.py 3 rating rules
   • pyhon preprocess.py 4 simplify test set
   • pyhon preprocess.py 5 filter test set

4. compile reasoning with g++ -std=c++11 -O2 reasoning.cpp, and run with ./a.out X

   1. ./a.out E denotes the embedding model is transE
   2. ./a.out H
   3. ./a.out R

   note that it will cost a long time with nearly three days, so you can use ./a.out X t for a small test.

experiment result

environment

LSB Version: core-4.1-amd64:core-4.1-noarch

Distributor ID: CentOS

Description: CentOS Linux release 7.7.1908 (Core)

Release: 7.7.1908

Codename: Core

cpu cores : 16

total used free shared buff/cache available

Mem: 125G 10G 106G 85M 9.0G 114G

result

Method	MR	MRR	Hits@10	Hits@5	Hits@3	Hits@1
TransE	70.30	45.77	74.27	64.44	55.79	29.98
EM-RBR(E)	68.36(up1.94)	50.01(+4.24)	76.23(+1.96)	67.84(+3.40)	60.62(+4.83)	34.44(+4.46)
TransH	72.56	45.81	74.01	64.09	55.53	30.37
TransH(EM-RBR)	70.72(up1.84)	52.39(+6.58)	76.52(+2.51)	68.28(+4.19)	61.13(+5.60)	38.82(+8.45)
TransR	55.98	47.88	77.04	68.01	59.47	31.10
TransR(EM-RBR)	55.47(up0.51)	51.93(+4.05)	78.35(+1.31)	70.54(+2.53)	63.42(+3.95)	35.86(+4.76)