PCFG models of linguistic tree representations
Computational Linguistics
A statistical parser for Czech
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
A parsing: fast exact Viterbi parse selection
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The Penn Treebank: annotating predicate argument structure
HLT '94 Proceedings of the workshop on Human Language Technology
On the parameter space of generative lexicalized statistical parsing models
On the parameter space of generative lexicalized statistical parsing models
Probabilistic CFG with latent annotations
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Online large-margin training of dependency parsers
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Arabic tokenization, part-of-speech tagging and morphological disambiguation in one fell swoop
ACL '05 Proceedings of the 43rd Annual Meeting on Association for 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
Morphology and reranking for the statistical parsing of Spanish
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Relational-realizational parsing
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Improved Arabic base phrase chunking with a new enriched POS tag set
Semitic '07 Proceedings of the 2007 Workshop on Computational Approaches to Semitic Languages: Common Issues and Resources
CATiB: the Columbia Arabic Treebank
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Products of random latent variable grammars
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Improving Arabic dependency parsing with lexical and inflectional morphological features
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
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
Handling unknown words in statistical latent-variable parsing models for Arabic, English and French
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Coarse-to-fine natural language processing
Coarse-to-fine natural language processing
Improving Arabic dependency parsing with form-based and functional morphological features
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
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We investigate how morphological features in the form of part-of-speech tags impact parsing performance, using Arabic as our test case. The large, fine-grained tagset of the Penn Arabic Treebank (498 tags) is difficult to handle by parsers, ultimately due to data sparsity. However, ad-hoc conflations of treebank tags runs the risk of discarding potentially useful parsing information. The main contribution of this paper is to describe several automated, language-independent methods that search for the optimal feature combination to help parsing. We first identify 15 individual features from the Penn Arabic Treebank tagset. Either including or excluding these features results in 32,768 combinations, so we then apply heuristic techniques to identify the combination achieving the highest parsing performance. Our results show a statistically significant improvement of 2.86% for vocalized text and 1.88% for unvocalized text, compared with the baseline provided by the Bikel-Bies Arabic POS mapping (and an improvement of 2.14% using product models for vocalized text, 1.65% for unvocalized text), giving state-of-the-art results for Arabic constituency parsing.