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simple_kbqa

A simple kbqa based on knowledge graph embedding

node and relation extracted via keyword based entity recognition multi relations extracted via part of speech with spacy graph search use pretrained graph embedding via rotatE model

  • Usage:

    • Train knowledge graph embedding

      git clone [email protected]:zhupengjia/KnowledgeGraphEmbedding.git
cd KnowledgeGraphEmbedding/codes
./run2.py --data_path=$DATA_PATH --model=RotatE --save_path=$SAVE_PATH --double_entity_embedding --cuda --hidden_dim=50

    • Run

      ./interact.py --checkpoint=$CHECKPOINTFILE --w2v_word2idx=$WORDEMBEDDINGLOOKUPFILE --w2v_idx2vec=$WORDEMBEDDINGWEIGHTFILE --backend restful

      word2vec lookup and weight file can be generated from script in example directory:

      cd example
./bert_to_wordvec.py