===== DATA =====
I provide FB15k datasets used for the task Knowledge Base Completion with the input format in [Download]
Dataset contains six files:
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train.txt: training file, format (e1, e2, rel).
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valid.txt: validation file, same format as train.txt
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test.txt: test file, same format as train.txt.
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entity2id.txt: all entities and corresponding ids, one per line.
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relation2id.txt: all relations and corresponding ids, one per line.
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e1_e2.txt: all top-500 entity pairs mentioned in the task entity prediction.
===== CODE =====
In the folder PTransE_add/, PTransE_mul/, PTransE_RNN/:
===== COMPILE =====
Just type make in the folder ./
== TRAINING ==
For training, You need follow the step below:
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Data preprocessing: python PCRA.py
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call Train_TransE_path in the corresponding directory. ./Train_TransE_path 1
== TESTING ==
For testing, You need follow the step below:
call Test_TransE_path in the corresponding directory. ./Test_TransE_path 1
It will evaluate on test.txt and report mean rank and Hits@1, the format is tier: head_mean_rank(Raw) head_hit@1(Raw), head_mean_rank(Filter) head_hit@1(Filter), tail_mean_rank(Raw) tail_hit@1(Raw), tail_mean_rank(Filter) tail_hit@1(Filter) relation_mean_rank(Raw) relation_hit@1(Raw), relation_mean_rank(Filter) relation_hit@1(Filter)