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GRASP: Grammar- and syntax-based pattern-finder for collocation and phrase learning
Journal article

GRASP: Grammar- and syntax-based pattern-finder for collocation and phrase learning

Mei-Hua Chen, Chung-Chi Huang, Shih-Ting Huang and Jason S. Chang
PACLIC 24 - Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation, pp.357-364
2010

Abstract

And inverted files Collocation Computer-assisted language learning Grammatical patterns Part-of-speech tagging
We introduce a method for learning to find the representative syntax-based context of a given collocation/phrase. In our approach, grammatical patterns are extracted for query terms aimed at accelerating lexicographers' and language learners' navigation through the word usage and learning process. The method involves automatically lemmatizing, part-of-speech tagging and shallowly parsing the sentences of a large-sized general corpus, and automatically constructing inverted files for quick search. At run-time, contextual grammar patterns are retrieved and presented to users with their corresponding statistical analyses. We present a prototype system, GRASP (grammar- and syntax-based pattern-finder), that applies the method to computer-assisted language learning. Preliminary results show that the extracted patterns not only resemble phrases in grammar books (e.g., make up one's mind) but help to assist the process of language learning and sentence composition/translation.

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