Abstract
We introduce an approach to word sense disambiguation and entity linking 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. Verb senses are disambiguated using a separate neural network model. Our results on noun and verb sense disambiguation as well as entity linking outperform all other submissions on the SemEval 2015 Task 13 for English.
Cite
CITATION STYLE
Weissenborn, D., Xu, F., & Uszkoreit, H. (2015). DFKI: Multi-objective Optimization for the Joint Disambiguation of Entities and Nouns & Deep Verb Sense Disambiguation. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 335–339). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2085
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