no code implementations • 13 Feb 2019 • Riyaz Ahmad Bhat, Irshad Ahmad Bhat, Dipti Misra Sharma
We investigate the problem of parsing conversational data of morphologically-rich languages such as Hindi where argument scrambling occurs frequently.
2 code implementations • NAACL 2018 • Irshad Ahmad Bhat, Riyaz Ahmad Bhat, Manish Shrivastava, Dipti Misra Sharma
We present a treebank of Hindi-English code-switching tweets under Universal Dependencies scheme and propose a neural stacking model for parsing that efficiently leverages part-of-speech tag and syntactic tree annotations in the code-switching treebank and the preexisting Hindi and English treebanks.
no code implementations • EACL 2017 • Irshad Ahmad Bhat, Riyaz Ahmad Bhat, Manish Shrivastava, Dipti Misra Sharma
In this paper, we propose efficient and less resource-intensive strategies for parsing of code-mixed data.
no code implementations • LREC 2016 • Maaz Anwar, Riyaz Ahmad Bhat, Dipti Sharma, Ashwini Vaidya, Martha Palmer, Tafseer Ahmed Khan
The present size of this Propbank is around 180, 000 tokens which is double-propbanked by the two annotators for simple predicates.
no code implementations • LREC 2014 • Riyaz Ahmad Bhat, Shahid Mushtaq Bhat, Dipti Misra Sharma
As the main contribution of this paper, we present an initial version of the Kashmiri Dependency Treebank.