Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting

Gathika Ratnayaka, Nisansa de Silva, Amal Shehan Perera, Ramesh Pathirana


Anthology ID:
2020.paclic-1.29
Volume:
Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation
Month:
October
Year:
2020
Address:
Hanoi, Vietnam
Editors:
Minh Le Nguyen, Mai Chi Luong, Sanghoun Song
Venue:
PACLIC
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
252–260
Language:
URL:
https://aclanthology.org/2020.paclic-1.29
DOI:
Bibkey:
Cite (ACL):
Gathika Ratnayaka, Nisansa de Silva, Amal Shehan Perera, and Ramesh Pathirana. 2020. Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting. In Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation, pages 252–260, Hanoi, Vietnam. Association for Computational Linguistics.
Cite (Informal):
Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting (Ratnayaka et al., PACLIC 2020)
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PDF:
https://aclanthology.org/2020.paclic-1.29.pdf
Data
SSTSST-5