NLATool: an Application for Enhanced Deep Text Understanding

Markus Gärtner, Sven Mayer, Valentin Schwind, Eric Hämmerle, Emine Turcan, Florin Rheinwald, Gustav Murawski, Lars Lischke, Jonas Kuhn


Abstract
Today, we see an ever growing number of tools supporting text annotation. Each of these tools is optimized for specific use-cases such as named entity recognition. However, we see large growing knowledge bases such as Wikipedia or the Google Knowledge Graph. In this paper, we introduce NLATool, a web application developed using a human-centered design process. The application combines supporting text annotation and enriching the text with additional information from a number of sources directly within the application. The tool assists users to efficiently recognize named entities, annotate text, and automatically provide users additional information while solving deep text understanding tasks.
Anthology ID:
C18-2026
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:
118–122
Language:
URL:
https://aclanthology.org/C18-2026
DOI:
Bibkey:
Cite (ACL):
Markus Gärtner, Sven Mayer, Valentin Schwind, Eric Hämmerle, Emine Turcan, Florin Rheinwald, Gustav Murawski, Lars Lischke, and Jonas Kuhn. 2018. NLATool: an Application for Enhanced Deep Text Understanding. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 118–122, Santa Fe, New Mexico. Association for Computational Linguistics.
Cite (Informal):
NLATool: an Application for Enhanced Deep Text Understanding (Gärtner et al., COLING 2018)
Copy Citation:
PDF:
https://aclanthology.org/C18-2026.pdf
Code
 interactionlab/nlatool