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Repurposing Theoretical Linguistic Data for Tool Development and Search

Fei Xia and William D. Lewis

Abstract

For the majority of the world’s languages, the number of linguistic resources (e.g., annotated corpora and parallel data) is very limited. Consequently, supervised methods, as well as many unsupervised methods, cannot be applied directly, leaving these languages largely untouched and unnoticed. In this paper, we describe the construction of a resource that taps the large body of linguistically analyzed language data that has made its way to the Web, and propose using this resource to bootstrap NLP tool development.

Details

Publication typeInproceedings
Published inProceedings of The Third International Joint Conference on Natural Language Processing (IJCNLP)
URLhttp://www.afnlp.org/
PublisherAsia Federation of Natural Language Processing
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