Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning

Jianpeng Cheng; Dimitri Kartsaklis; Edward Grefenstette

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arXiv · 1411.4116

Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning

Jianpeng Cheng·Dimitri Kartsaklis·Edward Grefenstette

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Abstract

This paper aims to explore the effect of prior disambiguation on neural network- based compositional models, with the hope that better semantic representations for text compounds can be produced. We disambiguate the input word vectors before they are fed into a compositional deep net. A series of evaluations shows the positive effect of prior disambiguation for such deep models.

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BibTeX RIS

Jianpeng Cheng, Dimitri Kartsaklis, Edward Grefenstette. 2014-11-15. Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning. https://arxiv.org/abs/1411.4116

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