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Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network
Distinguishing between antonyms and synonyms is a key task to achieve high
performance in NLP systems. While they are notoriously difficult to distinguish
by distributional co-occurrence models, pattern-based methods have proven
effective to differentiate between the relations. In this paper, we present a
novel neural network model AntSynNET that exploits lexico-syntactic patterns
from syntactic parse trees. In addition to the lexical and syntactic
information, we successfully integrate the distance between the related words
along the syntactic path as a new pattern feature. The results from
classification experiments show that AntSynNET improves the performance over
prior pattern-based methods.Comment: EACL 2017, 10 page
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