Two methods to incorporate local morphosyntactic features in Hindi dependency parsing

1st Workshop on Statistical Parsing of Morphologically-Rich Languages, SPMRL 2010 - Proceedings

Volumn , Issue , 2010, Pages 22-30

  Ambati, Bharat Ram ^a   Husain, Samar ^a   Jain, Sambhav ^a   Sharma, Dipti Misra ^a   Sangal, Rajeev ^a  

^a INTERNATIONAL INSTITUTE OF INFORMATION TECHNOLOGY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS;

BOUNDARY INFORMATION; DATA DRIVEN; DEPENDENCY PARSING; INFORMATION DISTANCE; MULTI-LAYERED; SENTENCE LEVEL; TREEBANKS;

SYNTACTICS;

EID: 84907344767     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. B. R. Ambati, P. Gadde, and K. Jindal. 2009a. Experiments in Indian Language Dependency Parsing. In Proc of the ICON09 NLP Tools Contest: Indian Language Dependency Parsing, pp 32-37.
2. B. R. Ambati, P. Gade, C. GSK and S. Husain. 2009b. Effect of Minimal Semantics on Dependency Parsing. In Proc of RANLP09 student paper workshop.
3. G. Attardi and F. Dell'Orletta. 2008. Chunking and Dependency Parsing. In Proc of LREC Workshop on Partial Parsing: Between Chunking and Deep Parsing. Marrakech, Morocco.
4. R. Begum, S. Husain, A. Dhwaj, D. Sharma, L. Bai, and R. Sangal. 2008. Dependency annotation scheme for Indian languages. In Proc of IJCNLP-2008.
5. A. Bharati, V. Chaitanya and R. Sangal. 1995. Natural Language Processing: A Paninian Perspective, Prentice-Hall of India, New Delhi.
6. A. Bharati, S. Husain, B. Ambati, S. Jain, D. Sharma, and R. Sangal. 2008. Two semantic features make all the difference in parsing accuracy. In Proc of ICON.
7. A. Bharati, R. Sangal, D. M. Sharma and L. Bai. 2006. AnnCorra: Annotating Corpora Guidelines for POS and Chunk Annotation for Indian Languages. Technical Report (TR-LTRC-31), LTRC, IIIT-Hyderabad.
8. A. Bharati, D. M. Sharma, S. Husain, L. Bai, R. Begam and R. Sangal. 2009a. AnnCorra: TreeBanks for Indian Languages, Guidelines for Annotating Hindi TreeBank. http://ltrc.iiit.ac.in/MachineTrans/research/tb/DSguidelines/DS-guidelines-ver2-28-05-09.pdf
9. A. Bharati, S. Husain, D. M. Sharma and R. Sangal. 2009b. Two stage constraint based hybrid approach to free word order language dependency parsing. In Proc. of IWPT.
10. A. Bharati, S. Husain, M. Vijay, K. Deepak, D. M. Sharma and R. Sangal. 2009c. Constraint Based Hybrid Approach to Parsing Indian Languages. In Proc of PACLIC 23. Hong Kong. 2009.
11. th IJCNLP.
12. Y.J. Chu and T.H. Liu. 1965. On the shortest arborescence of a directed graph. Science Sinica, 14:1396-1400.
13. J. Edmonds. 1967. Optimum branchings. Journal of Research of the National Bureau of Standards, 71B:233-240.
14. J. Eisner. 1996. Three new probabilistic models for dependency parsing: An exploration. In Proc of COLING-96, pp. 340-345.
15. G. Eryigit, J. Nivre, and K. Oflazer. 2008. Dependency Parsing of Turkish. Computational Linguistics 34(3), 357-389.
16. P. Gadde, K. Jindal, S. Husain, D. M. Sharma, and R. Sangal. 2010. Improving Data Driven Dependency Parsing using Clausal Information. In Proc of NAACL-HLT 2010, Los Angeles, CA.
17. E. Hajicova. 1998. Prague Dependency Treebank: From Analytic to Tectogrammatical Annotation. In Proc of TSD'98.
18. J. Hall, J. Nilsson, J. Nivre, G. Eryigit, B. Megyesi, M. Nilsson and M. Saers. 2007. Single Malt or Blended? A Study in Multilingual Parser Optimization. In Proc of the CoNLL Shared Task Session of EMNLP-CoNLL 2007, 933-939.
19. S. Husain. 2009. Dependency Parsers for Indian Languages. In Proc of ICON09 NLP Tools Contest: Indian Language Dependency Parsing. Hyderabad, India.
20. S. Husain, P. Gadde, B. Ambati, D. M. Sharma and R. Sangal. 2009. A modular cascaded approach to complete parsing. In Proc. of the COLIPS IALP.
21. P. Mannem, A. Abhilash and A. Bharati. 2009. LTAGspinal Treebank and Parser for Hindi. In Proc of International Conference on NLP, Hyderabad. 2009.
22. R. McDonald, K. Crammer, and F. Pereira. 2005. Online large-margin training of dependency parsers. In Proc of ACL. pp. 91-98.
23. R. McDonald, K. Lerman, and F. Pereira. 2006. Multilingual dependency analysis with a two-stage discriminative parser. In Proc of the Tenth (CoNLL-X), pp. 216-220.
24. R. McDonald and J. Nivre. 2007. Characterizing the errors of data-driven dependency parsing models. In Proc. of EMNLP-CoNLL.
25. J. Nivre, J. Hall, S. Kubler, R. McDonald, J. Nilsson, S. Riedel and D. Yuret. 2007a. The CoNLL 2007 Shared Task on Dependency Parsing. In Proc of EMNLP/CoNLL-2007.
26. J. Nivre, J. Hall, J. Nilsson, A. Chanev, G. Eryigit, S. Kübler, S. Marinov and E Marsi. 2007b. MaltParser: A language-independent system for data-driven dependency parsing. Natural Language Engineering, 13(2), 95-135.
27. J. Nivre and J. Nilsson. 2005. Pseudo-projective dependency parsing. In Proc. of ACL-2005, pp. 99-106.
28. Avinesh PVS and K. Gali. 2007. Part-Of-Speech Tagging and Chunking Using Conditional Random Fields and Transformation Based Learning. In Proc of the SPSAL workshop during IJCAI '07.
29. D. Seddah, M. Candito and B. Crabbé. 2009. Cross parser evaluation: a French Treebanks study. In Proc. of IWPT, 150-161.
30. R. Tsarfaty and K. Sima'an. 2008. Relational-Realizational Parsing. In Proc. of CoLing, 889-896.
31. A. Vaidya, S. Husain, P. Mannem, and D. M. Sharma. 2009. A karaka-based dependency annotation scheme for English. In Proc. of CICLing, 41-52.