Abstract
Due to the importance that verbs have in language an identification of their actants (obligatory complements) is important for understanding of the meaning of sentences. Usually, the solution of this problem in natural language processing is based on machine learning approaches, which are trained on large sets of tagged texts. We show that it is possible to work with other kind of sources, i.e., explanatory dictionaries. Dictionary definitions have patterns that provide enough information for identifying actants. We develop a heuristic approach in order to obtain this information and developed an algorithm for detection of actants in texts.
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Castro-Sánchez, N.A., Sidorov, G. (2010). Analysis of Definitions of Verbs in an Explanatory Dictionary for Automatic Extraction of Actants Based on Detection of Patterns. In: Hopfe, C.J., Rezgui, Y., Métais, E., Preece, A., Li, H. (eds) Natural Language Processing and Information Systems. NLDB 2010. Lecture Notes in Computer Science, vol 6177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13881-2_24
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DOI: https://doi.org/10.1007/978-3-642-13881-2_24
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