CFP last date
22 April 2024
Reseach Article

Exploring Semantic Information from Hindi Dependency Treebank for Resolving Pronominal Anaphora

Published on July 2015 by Seema Mahato, Ani Thomas
National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
Foundation of Computer Science USA
NCKITE2015 - Number 1
July 2015
Authors: Seema Mahato, Ani Thomas
f1b8567e-6ebd-4557-8e15-6fe19a0f0f89

Seema Mahato, Ani Thomas . Exploring Semantic Information from Hindi Dependency Treebank for Resolving Pronominal Anaphora. National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015). NCKITE2015, 1 (July 2015), 27-34.

@article{
author = { Seema Mahato, Ani Thomas },
title = { Exploring Semantic Information from Hindi Dependency Treebank for Resolving Pronominal Anaphora },
journal = { National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015) },
issue_date = { July 2015 },
volume = { NCKITE2015 },
number = { 1 },
month = { July },
year = { 2015 },
issn = 0975-8887,
pages = { 27-34 },
numpages = 8,
url = { /proceedings/nckite2015/number1/21479-2647/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%A Seema Mahato
%A Ani Thomas
%T Exploring Semantic Information from Hindi Dependency Treebank for Resolving Pronominal Anaphora
%J National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%@ 0975-8887
%V NCKITE2015
%N 1
%P 27-34
%D 2015
%I International Journal of Computer Applications
Abstract

Anaphora Resolution is exigent task in almost all NLP applications such as text summarization, machine translation, information extraction, question-answering systems, etc. A lot of work has been done for identifying and still more need to be done for finding the factors responsible for resolving the anaphoras in all languages. An attempt has been made to resolve Hindi pronominal anaphora using syntactic as well as semantic knowledge. The occurrence of particular case markers are found, which exhibit its connectivity with the pronouns leading to the anaphora resolution approach. An algorithm is designed taking into account the roles of subject, object and its impact on anaphora resolution for identifying the noun phrase antecedents of first and second person singular pronouns as well as for a third person singular pronoun and a reflexive pronoun. The algorithm applies on the inputted syntactic representation generated by a Hindi shallow parser. The authors have tested it on a text corpus containing 192 pronoun occurrences. The algorithm correctly resolved the antecedent of 145 pronouns (75. 5%) of these pronoun occurrences. Experiments on pronominal anaphora help in analyzing the complexity of problems under consideration and the results of the observations are presented.

References
  1. Mahato, S. and Thomas, A. 2015. Machine Learning Approach For Resolving Pronominal Anaphora Using Hindi Dependency Treebank, In Proceedings of BITCON-2015 Innovations For National Development. IJAERS/Vol. IV,Issue II,Jan. -March, 2015,Pages 155-159
  2. Bharati, A. , Bhargava Y. K. and Sangal, R. 1993. Reference and ellipsis in an Indian languages interface to database. Computer science and informatics, IIT Hyderabad, VOL 23; NUMBER 3, pages 60
  3. Prasad, R. and Strube, M. 2000. Discourse salience and pronoun resolution in Hindi. In Penn Working Papers in Linguistics: 6. 3, 189-208
  4. Sobha, L. and Patnaik, B. N. 2000. Vasisth: An anaphora resolution system for Malayalam and Hindi. In International Conference ACIDCA'2000
  5. Dutta, K. , Kaushik, S. and Prakash, N. 2004. Information extraction from Hindi texts. 1911-1914, LREC
  6. Dutta, K. , Prakash, N. , and Kaushik, S. 2008. Resolving Pronominal Anaphora in Hindi using Hobbs algorithm. Web Journal of Formal Computation and Cognitive Linguistics, 10
  7. Dutta, K. , Prakash, N. , and Kaushik, S. 2009. Application of pronominal divergence and anaphora resolution in English-Hindi machine translation. Research Journal "POLIBITS" Computer Science and Computer Engineering with Applications, VOL 39, pages 55-58
  8. Dutta, K. , Prakash, N. , and Kaushik, S. 2011. Machine learning approach for the classification of demonstrative pronouns for indirect anaphora in Hindi news items. Prague Bulletin of Mathematical Linguistics, VOL 95, pages 33-50
  9. Chatterji, S. , Dhar, A. , Barik, B. , Moumita PK, Sarkar, S. , and Basu, A. 2011. Anaphora resolution for Bengali, Hindi and Tamil using random tree algorithm in Weka. In Proceedings of ICON2011 NLP TOOL CONTEST: 9th International Conference on Natural Language Processing
  10. Pal, T. L. , Dutta, K. , and Singh, P. 2012. Anaphora resolution in Hindi: Issues and challenges. International Journal of Computer Applications, VOL 42; pages 18
  11. Dakwale, P. , Sharma, H. , and Sharma, D. 2012. Anaphora annotation in Hindi dependency treebank. 26th Pacific Asia Conference on Language, Information and Computation, 391–400
  12. Lakhmani, P. , and Singh, S. 2013. Anaphora resolution in Hindi language. International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 3, Number 7, pp. 609-616
  13. Dakwale, P. , Mujadia, V. , and Sharma, D. M. 2013. A hybrid approach for anaphora resolution in Hindi. International Joint Conference on Natural Language Processing, pages 977–981
  14. Singh, S. , Lakhmani, P. , Dr. Mathur, P. and Dr. Morwal, S. 2014. Comparative performance analysis of two anaphora resolution systems. International Journal in Foundations of Computer Science & Technology (IJFCST), Vol. 4, No. 2
  15. Lakhmani, P. , Singh, S. , Dr. Mathur, P. 2014. Gazetteer method for resolving pronominal anaphora in Hindi language. International Journal of Advances in Computer Science and Technology, Volume 3, No. 3
  16. Bharati, A. , Sangal, R. , Sharma, D. M. , and Bai, L. 2006. Anncorra: Annotating corpora guidelines for pos and chunk annotation for Indian languages. In Technical Report (TR-LTRC-31), LTRC, IIIT-Hyderabad.
  17. Bharati, A, Sharma, D. M. , Husain, S. , Bai, L. , Begum, R. , and Sangal, R. 2009. Anncorra: Treebanks for indian languages, guidelines for annotating Hindi treebank (version 2. 0). Retrieved from http://ltrc. iiit. ac. in/MachineTrans/research/tb/DS-guidelines / DS-guidelinesver2-28-05-09. pdf
  18. http://ltrc. iiit. ac. in/analyzer/hindi/
  19. http://ltrc. iiit. ac. in/full_analyzer/hindi/
  20. http://en. wikipedia. org/wiki/Natural_language_processing
  21. Jain, S. , Jain, N. , Tammewar, A. , Bhat, R. , A. , and Sharma, D. M. 2013. Exploring Semantic Information in Hindi WordNet for Hindi Dependency Parsing. In The Sixth International Joint Conference on Natural Language Processing
Index Terms

Computer Science
Information Sciences

Keywords

Anaphora Pronominal Resolution Dependency Treebank Case Marker.