Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
PCFG models of linguistic tree representations
Computational Linguistics
Compacting the Penn Treebank grammar
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
The Penn Treebank: annotating predicate argument structure
HLT '94 Proceedings of the workshop on Human Language Technology
A psychologically plausible and computationally effective approach to learning syntax
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
A psychologically plausible and computationally effective approach to learning syntax
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Exploiting heterogeneous treebanks for parsing
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
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In this paper we discuss the need for corpora with a variety of annotations to provide suitable resources to evaluate different Natural Language Processing systems and to compare them. A supervised machine learning technique is presented for translating corpora between syntactic formalisms and is applied to the task of translating the Penn Treebank annotation into a Categorial Grammar annotation. It is compared with a current alternative approach and results indicate annotation of broader coverage using a more compact grammar.