Paper Info
Title
SenTag: A Web-Based Tool for Semantic Annotation of Textual Documents.
Abstract
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.
Year
DOI
Venue
2022
10.1609/aaai.v36i11.21724
AAAI Conference on Artificial Intelligence
Keywords
DocType
Citations 
Text Annotation,Machine Learning,XML,Argumentation Graph
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Andrea Loreggia1277.81
Simone Mosco200.34
Alberto Zerbinati300.34