Contextualized Usage-Based Material Selection

In this paper, we combine several NLP-functionalities to organize examples drawn from corpora. The application’s primary target audience are language learners. Currently, authentic linguistic examples for a given keyword search are often organized alphabetically according to context. From this, it is not always clear which contextual regularities actually exist on a syntactic, collocational and semantic level. Showing information at different levels of abstraction will help with the discovery of linguistic regularities and thus improve linguistic understanding. Practically this translates in a system that groups retrieved results on syntactic grounds, after which the examples are further organized at the hand of semantic similarity within certain phrasal slots. Visualization algorithms are then used to show focused information in phrasal slots, laying bare semantic restrictions within the construction.

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