Generalized Tuning of Distributional Word Vectors for Monolingual and Cross-Lingual Lexical Entailment (P19-1)
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| Challenge: | Lexical entailment (LE) is a core asymmetric lexical relation that supports tasks like taxonomy induction and text generation. |
| Approach: | They propose a generalized Lexical ENtailment model that captures a specialization function allowing for LE-tuning of the entire distributional vector space and not only the vectors of words seen in lexical constraints. |
| Outcome: | The proposed model improves on graded LE and shows 20% improvement over state-of-the-art LE detection. |
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| Challenge: | Existing methods to detect lexical relations among distributionally similar words have been proposed to solve this problem. |
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