@inproceedings{Gartner:2018:NLA,
 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.},
 author = {Markus Gartner and Sven Mayer and Valentin Schwind and Eric Hammerle and Emine Turcan and Florin Rheinwald and Gustav Murawski and Lars Lischke and Jonas Kuhn},
 booktitle = {Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations},
 date = {2018-08-20},
 keywords = {computational linguistic, large high-resolution displays, wall-sized display},
 pages = {4},
 pubstate = {published},
 series = {COLING'18},
 title = {NLATool: An Application for Enhanced Deep Text Understanding},
 tppubtype = {inproceedings},
 url = {http://sven-mayer.com/wp-content/uploads/2018/06/gartner2018nlatool.pdf
https://github.com/interactionlab/NLATool},
 year = {2018}
}