SEMEME PREDICTION BASED ON NETWORK EMBEDDING AND PRE-TRAINING MODEL
Sememe is the core component of concept description in HowNet,and the predication of sememe description for new concepts is the key issue involved in automatic or semi-automatic expansion of HowNet.This paper proposes a sememe prediction method based on network embedding and the pre-training models.It realized the dynamic matching between the new concept and the candidate sememe by learning representation of the character-word-concept-sememe and their relationships in HowNet,and combining the pre-training language models to construct the partial"concept-sememe"relationship network.The predicted F1 value of the experimental results was 0.6237,which indicated that this method could solve the problem of semantic prediction of OOV words in HowNet more effectively.
SememePre-training language modelNetwork embedding
国家科技期刊平台
NSTL
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