A Multi-Platform Annotation Ecosystem for Domain Adaptation
Richard Eckart de Castilho, Nancy Ide, Jin-Dong Kim, Jan-Christoph Klie, Keith Suderman
Abstract
This paper describes an ecosystem consisting of three independent text annotation platforms. To demonstrate their ability to work in concert, we illustrate how to use them to address an interactive domain adaptation task in biomedical entity recognition. The platforms and the approach are in general domain-independent and can be readily applied to other areas of science.- Anthology ID:
- W19-4021
- Volume:
- Proceedings of the 13th Linguistic Annotation Workshop
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Annemarie Friedrich, Deniz Zeyrek, Jet Hoek
- Venue:
- LAW
- SIG:
- SIGANN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 189–194
- Language:
- URL:
- https://aclanthology.org/W19-4021
- DOI:
- 10.18653/v1/W19-4021
- Cite (ACL):
- Richard Eckart de Castilho, Nancy Ide, Jin-Dong Kim, Jan-Christoph Klie, and Keith Suderman. 2019. A Multi-Platform Annotation Ecosystem for Domain Adaptation. In Proceedings of the 13th Linguistic Annotation Workshop, pages 189–194, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- A Multi-Platform Annotation Ecosystem for Domain Adaptation (Eckart de Castilho et al., LAW 2019)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/W19-4021.pdf