Abstract
In this paper, we present a knowledge based approach to capture semantic representations from natural language for a class of applications where the representations of interest are known in advance. Our approach performs this task by generating phrases from these representations and matching these phrases against text using a set of syntactic and semantic transformations. The representation that best matches a piece of text is selected as its meaning. We evaluate our approach on a corpus of news articles collected from over 150 online news sources, and show how our approach performs well on capturing semantic representations from text.
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Yeh, P.Z., Farina, D.R., Kass, A. (2008). A Knowledge Based Approach for Capturing Rich Semantic Representations from Text. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85563-7_49
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DOI: https://doi.org/10.1007/978-3-540-85563-7_49
Publisher Name: Springer, Berlin, Heidelberg
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