DLCLSep 16, 2021

SenTag: a Web-based Tool for Semantic Annotation of Textual Documents

arXiv:2110.15062v1
Originality Synthesis-oriented
AI Analysis

This tool addresses the need for efficient and error-reduced semantic annotation in text analysis, though it is incremental as it builds on existing annotation methods.

The authors tackled the problem of semantic annotation of textual documents by developing SenTag, a web-based tool that facilitates tagging, reduces errors, and supports building argument graphs, with features for multi-user collaboration and annotator agreement assessment.

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 for errors in the output documents. Moreover, it allows 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.

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