The official Pytorch implementation of the paper RLogic: Recursive Logical Rule Learning from Knowledge Graphs
- entities.txt: a collection of entities in the KG
- relations.txt: a collection of relations in the KG
- facts.txt: a collection of facts in the KG
- train.txt: the model is trained to fit the triples in this data set
- valid.txt: create a blank file if no validation data is available
- test.txt: the learned ryles is evaluated on this data set for KG completion task
For example, this command train a RLogic on family dataset using gpu 0
python main.py --train --test --recur --get_rule --data family --topk 2400 --gpu 0
Each parameter means:
- --train: train the model
- --test: assign score to each rule in the rule space
- --recur: learn rules in recursive way
- --get_rule: output the learned rules
- --data: dataset
- --topk: number of the output rules