Papers with sememe-incorporated models

1 papers
Modeling Semantic Compositionality with Sememe Knowledge (P19-1)

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Challenge: Semantic compositionality (SC) is defined as the phenomenon that the meaning of a complex linguistic unit can be composed of the meanings of its constituents.
Approach: They propose to incorporate sememes into SC models and employ them in learning multiword expressions.
Outcome: The proposed models achieve significant performance boost compared to baseline methods without sememe knowledge.

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