Abstract
We present an algorithm which creates a German CCGbank by translating the syntax graphs in the German Tiger corpus into CCG derivation trees. The resulting corpus contains 46,628 derivations, covering 95% of all complete sentences in Tiger. Lexicons extracted from this corpus contain correct lexical entries for 94% of all known tokens in unseen text. © 2006 Association for Computational Linguistics.
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CITATION STYLE
Hockenmaier, J. (2006). Creating a CCGbank and a wide-coverage CCG lexicon for German. In COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Vol. 1, pp. 505–512). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1220175.1220239
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