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:
- 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)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/2020.paclic-1.29.pdf
- Data
- SST, SST-5