Free as in Free Word Order: An Energy Based Model for Word Segmentation and Morphological Tagging in Sanskrit

Amrith Krishna, Bishal Santra, Sasi Prasanth Bandaru, Gaurav Sahu, Vishnu Dutt Sharma, Pavankumar Satuluri, Pawan Goyal


Abstract
The configurational information in sentences of a free word order language such as Sanskrit is of limited use. Thus, the context of the entire sentence will be desirable even for basic processing tasks such as word segmentation. We propose a structured prediction framework that jointly solves the word segmentation and morphological tagging tasks in Sanskrit. We build an energy based model where we adopt approaches generally employed in graph based parsing techniques (McDonald et al., 2005a; Carreras, 2007). Our model outperforms the state of the art with an F-Score of 96.92 (percentage improvement of 7.06%) while using less than one tenth of the task-specific training data. We find that the use of a graph based approach instead of a traditional lattice-based sequential labelling approach leads to a percentage gain of 12.6% in F-Score for the segmentation task.
Anthology ID:
D18-1276
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Month:
October-November
Year:
2018
Address:
Brussels, Belgium
Editors:
Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
2550–2561
Language:
URL:
https://aclanthology.org/D18-1276
DOI:
10.18653/v1/D18-1276
Bibkey:
Cite (ACL):
Amrith Krishna, Bishal Santra, Sasi Prasanth Bandaru, Gaurav Sahu, Vishnu Dutt Sharma, Pavankumar Satuluri, and Pawan Goyal. 2018. Free as in Free Word Order: An Energy Based Model for Word Segmentation and Morphological Tagging in Sanskrit. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2550–2561, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Free as in Free Word Order: An Energy Based Model for Word Segmentation and Morphological Tagging in Sanskrit (Krishna et al., EMNLP 2018)
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