Date of Original Version

6-2015

Type

Conference Proceeding

Journal Title

Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

First Page

788

Last Page

798

Rights Management

Copyright 2015 Association for Computational Linguistics

Abstract or Description

We present a new algorithm for transforming dependency parse trees into phrase-structure parse trees. We cast the problem as structured prediction and learn a statistical model. Our algorithm is faster than traditional phrasestructure parsing and achieves 90.4% English parsing accuracy and 82.4% Chinese parsing accuracy, near to the state of the art on both benchmarks.

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Published In

Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 788-798.