Telugu Dependency Treebank
DOI:
https://doi.org/10.62760/iteecs.2.1.2023.41Keywords:
Natural language processing, Telugu language, Dependency parsing, Telugu tree bankAbstract
We discuss Telugu Language and Treebanks briefly in this work. Initially, we'll go over the Telugu language briefly. The paninian grammatical model utilized for Telugu dependency representation is then described. Following that, we explain Telugu treebanks and the various formats used to express these treebanks. We also discuss the Telugu language and its representation in the Telugu Dependency Treebank, and we give information on the Telugu language and the Telugu Dependency Treebank. Natural languages are often morphologically rich, and they create sentences in a variety of ways. Researchers have been investigating approaches to annotate text with linguistic knowledge since the advent of machine translation in the 1960s. Previous studies on Indian languages were done at the chunk level. The present shallow parser morphologically parses the input text to the chunk label. Researchers are considering working at the phrase level in the future. They broke the phrases down into smaller parts. The relationship between chunk heads is essential to proceed to sentence-level parsing. This results in reliance parsing.
References
R. Begum, S. Husain, A. Dhwaj, D. Misra Sharma, L. Bai, and R. Sangal “Dependency annotation scheme for Indian languages” In proceedings of the third international joint conference on natural language processing, Hyderabad, India, 2008
B. V. S. Kumari and R. R. Rao “Improving Telugu dependency parsing using combinatory categorial grammar supertags”, ACM Transactions on Asian and Low-Resource Language Information Processing, Vol. 14, No. 1, Article No. 3, 2015.
B. V. S. Kumari and R. R. Rao “A Hybrid Dependency Parsing Approach for Telugu Language”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, No. 9, pp: 664-668, 2015.
A. Bharati, R. Sangal, D. M. Sharma and L. Bai “AnnCorra: Annotating Corpora Guidelines for POS and Chunk Annotation for Indian Languages” In Technical Report (TR-LTRC-31), LTRC, IIIT-Hyderabad, 2006.
A. Bharati, R. Sangal and D. M. Sharma SSF: Shakti Standard Format Guide. In Technical Report (TRLTRC-33), LTRC, IIIT-Hyderabad, 2007.
B. V. S. Kumari and R. R. Rao “Improving Indian Language Dependency Parsing by Combining Transition-based and Graph-based Parsers”, International Journal of Computer Applications Vol. 115, No. 5, pp. 13-17, 2015.
A. Bharati, S. Husain, D. M. Sharma and R. Sangal “A Two-Stage Constraint Based Dependency Parser for Free Word Order Languages”, In Proceedings of the COLIPS International Conference on Asian Language Processing, Chiang Mai, Thailand, 2008.
B. V. S. Kumari, A. G. Prasaad, M. Susmitha, and R. Bhatnagar “Exploring Different Approaches for Parsing Telugu”, In proceedings Advances in Intelligent system and computing, Vol: 921, pp-546-555, 2019.
A. Bharati, P. Mannem and D. M. Sharma “Hindi Parsing Shared Task”, In Proceedings of COLING-2012, Workshop on Machine Translation and Parsing in Indian Languages, IIT, Mumbai. India, 2012.
B. V. S. Kumari and R. R. Ramisetty “Hindi Dependency Parsing using a combined model of Malt and MST”, In Proceedings of the Workshop on Machine Translation and Parsing in Indian Languages, held at IIT, pp. 171-178, Mumbai in 2012.
J. Bos, C. Bosco and A. Mazzei “Converting a Dependency Tree-bank to a Categorial Grammar Treebank for Italian”, In M. Passarotti, Adam Przepiorkowski,´ Proceedings of the Eighth International Workshop on Treebanks and Linguistic Theories, pp. 27–38, Milan, Italy, 2009.
R. R. Rajeswara and B. V. S. Kumari “Two approaches for incorporating linguistic constraints to improve the usability of Telugu dependency parser”, International Journal of Applied Pattern Recognition, Vol. 3, No. 2 pp: 135-144, 2016.
S. Buchholz and E. Marsi “CoNLL-X shared task on multilingual dependency parsing”, In Proceedings of the Tenth Conference on Computational Natural Language Learning, pp.149–164, New York City, New York, 2006.
A. Cahill, B. Gyawali and J. Bruno “Self-training for parsing learner text”, In Proceedings of the First Joint Workshop on Statistical Parsing of Morphologically Rich Languages and Syntactic Analysis of Non-Canonical Languages, pp: 66–73, Dublin, Ireland, 2014.
B. V. S. Kumari and R. R. Rao “Improving the Usability of Statistical Parsers by Incorporating Linguistic Constraints”, International Journal of Electronics Communication & Computer Engineering, Vol. 4, No. 6, pp:102-105, 2013.
D. Deepthi and B. V. S. Kumari “Identification and Recognition of Facial expression using CNN Algorithm”, Turkish Journal of Computer and Mathematics Education, Vol. 12 No. 6, pp. 5496-5504, 2021.
B. R. Ambati, P. Gadde and K. Jindal “Experiments in Indian Language Dependency Parsing”, In Proceedings of ICON09 NLP Tools Contest: Indian Language Dependency Parsing, Hyderabad, India, 2009.
R. Cakici “Automatic induction of a CCG grammar for Turkish”, In Proceedings of the ACL Student Research Workshop, pp. 73–78, Ann Arbor, Michigan, 2005.
R. Cak?c? “Parser Models for a Highly Inflected Language”, PhD thesis, University of Edinburgh, UK, 2009.
B. V. S. Kumari and R. R. Rao “Telugu dependency parsing using different statistical parsers”, Journal of King Saud University-Computer and Information Sciences, Vol. 29, No. 1, pp: 134-140, 2017.
S. Clark, and J. R. Curran. "Wide-coverage efficient statistical parsing with CCG and log-linear models." Computational Linguistics, Vol. 33, No. 4, pp: 493-552, 2007.
S. V. Kumar, M. Nagaratna and L. H. Marrivada, “Task scheduling in cloud computing using PSO algorithm. In Smart Intelligent Computing and Applications”, Proceedings of Fifth International Conference on Smart Computing and Informatics, pp: 541-550, 2021.
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