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. © 2008 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Yeh, P. Z., Farina, D. R., & Kass, A. (2008). A knowledge based approach for capturing rich semantic representations from text. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5177 LNAI, pp. 375–383). Springer Verlag. https://doi.org/10.1007/978-3-540-85563-7_49
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