In this paper, we present a novel approach to joint word sense disambiguation (WSD) and entity linking (EL) that combines a set of complementary objectives in an extensible multi-objective formalism. During disambiguation the system performs continuous optimization to find optimal probability distributions over candidate senses. The performance of our system on nominal WSD as well as EL improves state-ofthe-art results on several corpora. These improvements demonstrate the importance of combining complementary objectives in a joint model for robust disambiguation.
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Multi-Objective Optimization for the Joint Disambiguation of Nouns and Named Entities
Semantic Scholar · Computer Science · 2015
Abstract
In this paper, we present a novel approach to joint word sense disambiguation (WSD) and entity linking (EL) that combines a set of complementary objectives in an extensible multi-objective formalism. During disambiguation the system performs continuous optimization to find optimal probability distributions over candidate senses. The performance of our system on nominal WSD as well as EL improves state-ofthe-art results on several corpora. These improvements demonstrate the importance of combining complementary objectives in a joint model for robust disambiguation.
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