SenTag: A Web-Based Tool for Semantic Annotation of Textual Documents
DOI:
https://doi.org/10.1609/aaai.v36i11.21724Keywords:
Text Annotation, Machine Learning, XML, Argumentation GraphAbstract
In this work, we present SenTag, a lightweight web-based tool focused on semantic annotation of textual documents. The platform allows multiple users to work on a corpus of documents. The tool enables to tag a corpus of documents through an intuitive and easy-to-use user interface that adopts the Extensible Markup Language (XML) as output format. The main goal of the application is two-fold: facilitating the tagging process and reducing or avoiding errors in the output documents. It allows also to identify arguments and other entities that are used to build an arguments graph. It is also possible to assess the level of agreement of annotators working on a corpus of text.Downloads
Published
2022-06-28
How to Cite
Loreggia, A., Mosco, S., & Zerbinati, A. (2022). SenTag: A Web-Based Tool for Semantic Annotation of Textual Documents. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13191-13193. https://doi.org/10.1609/aaai.v36i11.21724
Issue
Section
AAAI Demonstration Track