首页> 外文会议>International workshop on semantic evaluation;Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies >DFKI: Multi-objective Optimization for the Joint Disambiguation of Entities and Nouns Deep Verb Sense Disambiguation
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DFKI: Multi-objective Optimization for the Joint Disambiguation of Entities and Nouns Deep Verb Sense Disambiguation

机译:DFKI:实体和名词联合歧义消除和多动词语义歧义消除的多目标优化

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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 Se-mEval 2015 Task 13 for English.
机译:我们介绍一种解决词义歧义和实体链接的方法,该方法在可扩展的多目标形式主义中结合了一系列互补的目标。在消歧期间,系统执行连续优化以找到候选感官上的最佳概率分布。使用独立的神经网络模型可以消除动词的歧义。我们在名词和动词意义上的歧义化以及实体链接的结果优于2015年Se-mEval任务13英文版的所有其他论文。

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