Unsupervised Deep Structured Semantic Models for Commonsense Reasoning

North American Chapter of the Association for Computational Linguistics, pp. 882-891, 2019.

Cited by: 5|Bibtex|Views128|DOI:https://doi.org/10.18653/v1/n19-1094
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Commonsense reasoning is fundamental to natural language understanding. While traditional methods rely heavily on human-crafted features and knowledge bases, we explore learning commonsense knowledge from a large amount of raw text via unsupervised learning. We propose two neural network models based on the Deep Structured Semantic Models...More

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