CCGbank: A Corpus of CCG Derivations and Dependency Structures Extracted from the Penn Treebank
Author(s) -
Julia Hockenmaier,
Mark Steedman
Publication year - 2007
Publication title -
computational linguistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.314
H-Index - 98
eISSN - 1530-9312
pISSN - 0891-2017
DOI - 10.1162/coli.2007.33.3.355
Subject(s) - treebank , computer science , natural language processing , dependency (uml) , combinatory categorial grammar , artificial intelligence , parsing , annotation , dependency grammar , rule based machine translation , tree adjoining grammar , context free grammar
This article presents an algorithm for translating the Penn Treebank into a corpus of Combinatory Categorial Grammar (CCG) derivations augmented with local and long-range word-word dependencies. The resulting corpus, CCGbank, includes 99.4% of the sentences in the Penn Treebank. It is available from the Linguistic Data Consortium, and has been used to train wide-coverage statistical parsers that obtain state-of-the-art rates of dependency recovery. In order to obtain linguistically adequate CCG analyses, and to eliminate noise and inconsistencies in the original annotation, an extensive analysis of the constructions and annotations in the Penn Treebank was called for, and a substantial number of changes to the Treebank were necessary. We discuss the implications of our findings for the extraction of other linguistically expressive grammars from the Treebank, and for the design of future treebanks.
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