Predicate-argument analysis to build a phraseology module and to increase conceptual relation expressiveness

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Abstract

EcoLexicon, a multilingual and multimodal terminological knowledge base (TKB) on the environment, needs improvements: more expressive non-hierarchical relations and a phraseology module consistent with knowledge representation in the other modules of the TKB. Both issues must be addressed by analyzing predicate-argument structure in text. In this paper, we explain our methodology for predicate-argument analysis with the case study on the conceptual relation affects. We take a semi-automatic approach to extract term-verb-term collocates with Sketch Engine [1]. Then the verbs are classified according to the lexical domains proposed by Faber & Mairal [2] and the arguments in conceptual categories based on the knowledge contained in EcoLexicon. To validate the lexical domains and conceptual categories, an automatic clustering method based on word2vec [3] is applied. The analysis of verbs and arguments contributes to the refinement of our semantic relations and categories as well as to the population of the phraseological module.

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Reimerink, A., & León-Araúz, P. (2017). Predicate-argument analysis to build a phraseology module and to increase conceptual relation expressiveness. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10596 LNAI, pp. 176–190). Springer Verlag. https://doi.org/10.1007/978-3-319-69805-2_13

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