The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation

Jan-Christoph Klie, Michael Bugert, Beto Boullosa, Richard Eckart de Castilho, Iryna Gurevych


Abstract
We introduce INCEpTION, a new annotation platform for tasks including interactive and semantic annotation (e.g., concept linking, fact linking, knowledge base population, semantic frame annotation). These tasks are very time consuming and demanding for annotators, especially when knowledge bases are used. We address these issues by developing an annotation platform that incorporates machine learning capabilities which actively assist and guide annotators. The platform is both generic and modular. It targets a range of research domains in need of semantic annotation, such as digital humanities, bioinformatics, or linguistics. INCEpTION is publicly available as open-source software.
Anthology ID:
C18-2002
Volume:
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico
Editor:
Dongyan Zhao
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5–9
Language:
URL:
https://aclanthology.org/C18-2002
DOI:
Bibkey:
Cite (ACL):
Jan-Christoph Klie, Michael Bugert, Beto Boullosa, Richard Eckart de Castilho, and Iryna Gurevych. 2018. The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 5–9, Santa Fe, New Mexico. Association for Computational Linguistics.
Cite (Informal):
The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation (Klie et al., COLING 2018)
Copy Citation:
PDF:
https://aclanthology.org/C18-2002.pdf
Code
 inception-project/inception