New submission on ISA-15 (2019)

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The following new publication have been accepted:

Fifteenth Joint ACL – ISO Workshop on Interoperable Semantic Annotation, ISA-15 (2019)

  • [1] TextAnnotator: A flexible framework for semantic annotations

[1] [pdf] G. Abrami, A. Mehler, A. Lücking, E. Rieb, and P. Helfrich, “TextAnnotator: A flexible framework for semantic annotations,” in Proceedings of the Fifteenth Joint ACL – ISO Workshop on Interoperable Semantic Annotation, (ISA-15), 2019.
[Bibtex]
@InProceedings{Abrami:et:al:2019,
  Author         = {Abrami, Giuseppe and Mehler, Alexander and Lücking, Andy and Rieb, Elias and Helfrich, Philipp},
  Title          = {{TextAnnotator}: A flexible framework for semantic annotations},
  BookTitle      = {Proceedings of the Fifteenth Joint ACL - ISO Workshop on Interoperable Semantic Annotation, (ISA-15)},
  Series         = {ISA-15},
  location       = {Gothenburg, Sweden},
  month     = {May},
  pdf      = {https://www.texttechnologylab.org/wp-content/uploads/2019/04/TextAnnotator_IWCS_Göteborg.pdf},
  year           = 2019,
  abstract   ="Modern annotation tools should meet at least the following general requirements: they can handle diverse data and annotation levels within one tool, and they support the annotation process with automatic (pre-)processing outcomes as much as possible. We developed a framework that meets these general requirements and that enables versatile and browser-based annotations of texts, the TextAnnotator. It combines NLP methods of pre-processing with methods of flexible post-processing. Infact, machine learning (ML) requires a lot of training and test data, but is usually far from achieving perfect results. Producing high-level annotations for ML and post-correcting its results are therefore necessary. This is the purpose of TextAnnotator, which is entirely implemented in ExtJS and provides a range of interactive visualizations of annotations. In addition, it allows for flexibly integrating knowledge resources, e.g. in the course of post-processing named entity recognition. The paper describes TextAnnotator’s architecture together with three use cases: annotating temporal structures, argument structures and named entity linking."
}