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Hannotate: Flexible Annotation for Text Analytics from Anywhere

conference contribution
posted on 2024-11-03, 15:22 authored by Tan-Tai To, Hoang Dao, Huyen Nguyen, Thanh-Ha Do, Anh HoangAnh Hoang
Data annotation is a critical but the most expensive step in any text analytics project. There have been several frameworks built for enabling and easing this step. Most of these frameworks are however either not easy to be configured to specific users’ needs, have no functionalities for annotating text pairs, or lack of efficient mechanism for data management and progress monitoring. Moreover, they have mostly no graphical user interfaces that are specifically designed for mobile devices. In this paper, we introduce Hannotate, a highly flexible, lightweight web-based framework that provides functionalities for a wide range of text annotation from both desktop and mobile devices. Our framework inherits the advantages of the typical existing ones while allowing users to easily customize the annotation work according to their demand and budget. The framework also supports users in managing data, monitoring the progress, and giving feedback to annotators.

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Related Materials

  1. 1.
    DOI - Is published in 10.1007/978-3-031-43458-7_24
  2. 2.
    ISBN - Is published in 9783031434570 (urn:isbn:9783031434570)

Start page

128

End page

132

Total pages

5

Outlet

Proceedings of the 20th Extended Semantic Web Conference (ESWC 2023)

Editors

Catia Pesquita, Hala Skaf-Molli, Vasilis Efthymiou, Sabrina Kirrane, Axel Ngonga, Diego Collarana, Renato Cerqueira · Mehwish Alam, Cassia Trojahn, Sven Hertling

Name of conference

Lecture Notes in Computer Science Volume 13998

Publisher

Springer

Place published

Cham, Switzerland

Start date

2023-05-28

End date

2023-06-01

Language

English

Copyright

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

Former Identifier

2006127021

Esploro creation date

2024-03-14

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