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Knowledge Extraction on Multidimensional Concepts: Corpus Pattern Analysis (CPA) and Concordances

Multidimensionality of concepts in multidisciplinary domains is a problem terminographers have to deal with. We apply Corpus Pattern Analysis (CPA; Pustejovsky, Hanks, & Rumshisky, 2004) to extract conceptual dimensions according to context. The dynamic nature of these concepts is exemplified with the case study of SAND. On the other hand, knowledge patterns (KPs) often convey different conceptual relations and are therefore polysemic structures. The development of pattern-based constraints can help to disambiguate them and at the same time avoid conceptual noise, which would be a first step towards the systematization of automatic knowledge extraction. Two KPs are analyzed in detail: rang* from, which conveys the conceptual relation is_a, and the polysemic KP formed by.