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Incorporating Chinese Characters of Words for Lexical Sememe Prediction

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Figure

Figure 1: Sememes of the word “铁匠” (iron-smith) in HowNet, where occupation, human andindustrial can be inferred by both external (con-texts) and internal (characters) information, whilemetal is well-captured only by the internal infor-mation within the character “ 铁” (iron).
Figure 3:An example of adopting multiple-prototype character embeddings. The numbers arethe cosine distances
Figure 4: The illustration of model ensembling.
Table 1: Evaluation results on sememe prediction.The result of SPWCF + SPCSE is bold for com-paring with other methods (SPWCF and SPCSE)which use only internal information.
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