Rajeev Sangal


2020

pdf bib
Proceedings of the 17th International Conference on Natural Language Processing (ICON)
Pushpak Bhattacharyya | Dipti Misra Sharma | Rajeev Sangal
Proceedings of the 17th International Conference on Natural Language Processing (ICON)

2018

pdf bib
Proceedings of the 15th International Conference on Natural Language Processing
Gurpreet Singh Lehal | Dipti Misra Sharma | Rajeev Sangal
Proceedings of the 15th International Conference on Natural Language Processing

2016

pdf bib
IIT (BHU) Submission on the CoNLL-2016 Shared Task: Shallow Discourse Parsing using Semantic Lexicons
Manpreet Kaur | Nishu Kumari | Anil Kumar Singh | Rajeev Sangal
Proceedings of the CoNLL-16 shared task

pdf bib
Proceedings of the 13th International Conference on Natural Language Processing
Dipti Misra Sharma | Rajeev Sangal | Anil Kumar Singh
Proceedings of the 13th International Conference on Natural Language Processing

2015

pdf bib
Proceedings of the 12th International Conference on Natural Language Processing
Dipti Misra Sharma | Rajeev Sangal | Elizabeth Sherly
Proceedings of the 12th International Conference on Natural Language Processing

2014

pdf bib
Proceedings of the 11th International Conference on Natural Language Processing
Dipti Misra Sharma | Rajeev Sangal | Jyoti D. Pawar
Proceedings of the 11th International Conference on Natural Language Processing

pdf bib
SSF: A Common Representation Scheme for Language Analysis for Language Technology Infrastructure Development
Akshar Bharati | Rajeev Sangal | Dipti Misra Sharma | Anil Kumar Singh
Proceedings of the Workshop on Open Infrastructures and Analysis Frameworks for HLT

2013

pdf bib
A Novel Approach Towards Incorporating Context Processing Capabilities in NLIDB System
Arjun Akula | Rajeev Sangal | Radhika Mamidi
Proceedings of the Sixth International Joint Conference on Natural Language Processing

pdf bib
Stance Classification in Online Debates by Recognizing Users’ Intentions
Sarvesh Ranade | Rajeev Sangal | Radhika Mamidi
Proceedings of the SIGDIAL 2013 Conference

2012

pdf bib
Intra-Chunk Dependency Annotation : Expanding Hindi Inter-Chunk Annotated Treebank
Prudhvi Kosaraju | Bharat Ram Ambati | Samar Husain | Dipti Misra Sharma | Rajeev Sangal
Proceedings of the Sixth Linguistic Annotation Workshop

2011

pdf bib
Clausal parsing helps data-driven dependency parsing: Experiments with Hindi
Samar Husain | Phani Gadde | Joakim Nivre | Rajeev Sangal
Proceedings of 5th International Joint Conference on Natural Language Processing

pdf bib
Proceedings of the 2nd Workshop on South Southeast Asian Natural Language Processing (WSSANLP)
Rajeev Sangal | M. G. Abbas Malik
Proceedings of the 2nd Workshop on South Southeast Asian Natural Language Processing (WSSANLP)

pdf bib
Linguistically Rich Graph Based Data Driven Parsing For Hindi
Samar Husain | Raghu Pujitha Gade | Rajeev Sangal
Proceedings of the Second Workshop on Statistical Parsing of Morphologically Rich Languages

2010

pdf bib
Grammar Extraction from Treebanks for Hindi and Telugu
Prasanth Kolachina | Sudheer Kolachina | Anil Kumar Singh | Samar Husain | Viswanath Naidu | Rajeev Sangal | Akshar Bharati
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Grammars play an important role in many Natural Language Processing (NLP) applications. The traditional approach to creating grammars manually, besides being labor-intensive, has several limitations. With the availability of large scale syntactically annotated treebanks, it is now possible to automatically extract an approximate grammar of a language in any of the existing formalisms from a corresponding treebank. In this paper, we present a basic approach to extract grammars from dependency treebanks of two Indian languages, Hindi and Telugu. The process of grammar extraction requires a generalization mechanism. Towards this end, we explore an approach which relies on generalization of argument structure over the verbs based on their syntactic similarity. Such a generalization counters the effect of data sparseness in the treebanks. A grammar extracted using this system can not only expand already existing knowledge bases for NLP tasks such as parsing, but also aid in the creation of grammars for languages where none exist. Further, we show that the grammar extraction process can help in identifying annotation errors and thus aid in the task of the treebank validation.

pdf bib
Two Methods to Incorporate ’Local Morphosyntactic’ Features in Hindi Dependency Parsing
Bharat Ram Ambati | Samar Husain | Sambhav Jain | Dipti Misra Sharma | Rajeev Sangal
Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages

pdf bib
On the Role of Morphosyntactic Features in Hindi Dependency Parsing
Bharat Ram Ambati | Samar Husain | Joakim Nivre | Rajeev Sangal
Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages

pdf bib
A Discriminative Approach for Dependency Based Statistical Machine Translation
Sriram Venkatapathy | Rajeev Sangal | Aravind Joshi | Karthik Gali
Proceedings of the 4th Workshop on Syntax and Structure in Statistical Translation

pdf bib
Improving Data Driven Dependency Parsing using Clausal Information
Phani Gadde | Karan Jindal | Samar Husain | Dipti Misra Sharma | Rajeev Sangal
Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics

pdf bib
Coupling Statistical Machine Translation with Rule-based Transfer and Generation
Arafat Ahsan | Prasanth Kolachina | Sudheer Kolachina | Dipti Misra | Rajeev Sangal
Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers

In this paper, we present the insights gained from a detailed study of coupling a highly modular English-Hindi RBMT system with a standard phrase-based SMT system. Coupling the RBMT and SMT systems at various stages in the RBMT pipeline, we observe the effects of the source transformations at each stage on the performance of the coupled MT system. We propose an architecture that systematically exploits the structural transfer and robust generation capabilities of the RBMT system. Working with the English-Hindi language pair, we show that the coupling configurations explored in our experiments help address different aspects of the typological divergence between these languages. In spite of working with very small datasets, we report significant improvements both in terms of BLEU (7.14 and 0.87 over the RBMT and the SMT baselines respectively) and subjective evaluation (relative decrease of 17% in SSER).

2009

pdf bib
Constraint Based Hybrid Approach to Parsing Indian Languages
Akshar Bharati | Samar Husain | Meher Vijay | Kalyan Deepak | Dipti Misra Sharma | Rajeev Sangal
Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation, Volume 2

pdf bib
Two stage constraint based hybrid approach to free word order language dependency parsing
Akshar Bharati | Samar Husain | Dipti Misra | Rajeev Sangal
Proceedings of the 11th International Conference on Parsing Technologies (IWPT’09)

pdf bib
All Words Unsupervised Semantic Category Labeling for Hindi
Siva Reddy | Abhilash Inumella | Rajeev Sangal | Soma Paul
Proceedings of the International Conference RANLP-2009

2008

pdf bib
Dependency Annotation Scheme for Indian Languages
Rafiya Begum | Samar Husain | Arun Dhwaj | Dipti Misra Sharma | Lakshmi Bai | Rajeev Sangal
Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-II

2005

pdf bib
A Hybrid Approach to Single and Multiple PP Attachment Using WordNet
Akshar Bharathi | U. Rohini | P. Vishnu | S.M. Bendre | Rajeev Sangal
Second International Joint Conference on Natural Language Processing: Full Papers

pdf bib
HMM Based Chunker for Hindi
Akshay Singh | Sushma Bendre | Rajeev Sangal
Companion Volume to the Proceedings of Conference including Posters/Demos and tutorial abstracts

2002

pdf bib
AnnCorra: Building Tree-banks in Indian Languages
Akshar Bharati | Rajeev Sangal | Vineet Chaitanya | Amba Kulkarni | Dipti Misra Sharma | K.V. Ramakrishnamacharyulu
COLING-02: The 3rd Workshop on Asian Language Resources and International Standardization

2000

pdf bib
Panel: Computational Linguistics in India: An Overview
Akshar Bharati | Vineet Chaitanya | Rajeev Sangal
Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics

1993

pdf bib
Parsing Free Word Order Languages in the Paninian Framework
Akshar Bharati | Rajeev Sangal
31st Annual Meeting of the Association for Computational Linguistics

1990

pdf bib
A Karaka Based Approach to Parsing of Indian Languages
Akshar Bharati | Rajeev Sangal
COLING 1990 Volume 3: Papers presented to the 13th International Conference on Computational Linguistics

1989

pdf bib
Parsing Generalized Phrase Structure Grammar with Dynamic Expansion
Navin Budhiraja | Subrata Mitra | Harish Karnick | Rajeev Sangal
Proceedings of the First International Workshop on Parsing Technologies

A parser is described here based on the Cocke-Young-Kassami algorithm which uses immediate dominance and linear precedence rules together with various feature inheritance conventions. The meta rules in the grammar are not applied beforehand but only when needed. This ensures that the rule set is kept to a minimum. At the same time, determining what rule to expand by applying which meta-rule is done in an efficient manner using the meta-rule reference table. Since this table is generated during “compilation” stage, its generation does not add to parsing time.