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
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
A statistical parser for Czech
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Head-Driven Statistical Models for Natural Language Parsing
Computational Linguistics
Learning accurate, compact, and interpretable tree annotation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Efficient parsing of highly ambiguous context-free grammars with bit vectors
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Design of a multi-lingual, parallel-processing statistical parsing engine
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Integrated morphological and syntactic disambiguation for Modern Hebrew
COLING ACL '06 Proceedings of the 21st International Conference on computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
When is self-training effective for parsing?
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Relational-realizational parsing
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Parsing three German treebanks: lexicalized and unlexicalized baselines
PaGe '08 Proceedings of the Workshop on Parsing German
The PaGe 2008 shared task on parsing German
PaGe '08 Proceedings of the Workshop on Parsing German
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Statistical parsing with a context-free grammar and word statistics
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Application of different techniques to dependency parsing of Basque
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Modeling morphosyntactic agreement in constituency-based parsing of modern Hebrew
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Word segmentation, unknown-word resolution, and morphological agreement in a hebrew parsing system
Computational Linguistics
Multilingual joint parsing of syntactic and semantic dependencies with a latent variable model
Computational Linguistics
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Applying statistical parsers developed for English to languages with freer word-order has turned out to be harder than expected. This paper investigates the adequacy of different statistical parsing models for dealing with a (relatively) free word-order language. We show that the recently proposed Relational-Realizational (RR) model consistently outperforms state-of-the-art Head-Driven (HD) models on the Hebrew Treebank. Our analysis reveals a weakness of HD models: their intrinsic focus on configurational information. We conclude that the form-function separation ingrained in RR models makes them better suited for parsing nonconfigurational phenomena.