Within-Between Lexical Relation Classification
We propose the novel \textit{Within-Between} Relation model for recognizing lexical-semantic relations between words. Our model integrates relational and distributional signals, forming an effective sub-space representation for each relation. We show that the proposed model is competitive and outperforms other baselines, across various benchmarks.
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