Three new probabilistic models for dependency parsing: an exploration
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Online large-margin training of dependency parsers
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Pseudo-projective dependency parsing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Computational Linguistics
A Karaka Based Annotation Scheme for English
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
Multilingual dependency analysis with a two-stage discriminative parser
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Relational-realizational parsing
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Two stage constraint based hybrid approach to free word order language dependency parsing
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Cross parser evaluation and tagset variation: a French treebank study
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
A multi-representational and multi-layered treebank for Hindi/Urdu
ACL-IJCNLP '09 Proceedings of the Third Linguistic Annotation Workshop
A Modular Cascaded Approach to Complete Parsing
IALP '09 Proceedings of the 2009 International Conference on Asian Language Processing
Improving data driven dependency parsing using clausal information
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Statistical parsing of morphologically rich languages (SPMRL): what, how and whither
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Identification of conjunct verbs in hindi and its effect on parsing accuracy
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
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In this paper we explore two strategies to incorporate local morphosyntactic features in Hindi dependency parsing. These features are obtained using a shallow parser. We first explore which information provided by the shallow parser is most beneficial and show that local morphosyntactic features in the form of chunk type, head/non-head information, chunk boundary information, distance to the end of the chunk and suffix concatenation are very crucial in Hindi dependency parsing. We then investigate the best way to incorporate this information during dependency parsing. Further, we compare the results of various experiments based on various criterions and do some error analysis. All the experiments were done with two data-driven parsers, MaltParser and MSTParser, on a part of multi-layered and multi-representational Hindi Treebank which is under development. This paper is also the first attempt at complete sentence level parsing for Hindi.