Giuseppe Abrami


2020

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TextAnnotator: A UIMA Based Tool for the Simultaneous and Collaborative Annotation of Texts
Giuseppe Abrami | Manuel Stoeckel | Alexander Mehler
Proceedings of the 12th Language Resources and Evaluation Conference

The annotation of texts and other material in the field of digital humanities and Natural Language Processing (NLP) is a common task of research projects. At the same time, the annotation of corpora is certainly the most time- and cost-intensive component in research projects and often requires a high level of expertise according to the research interest. However, for the annotation of texts, a wide range of tools is available, both for automatic and manual annotation. Since the automatic pre-processing methods are not error-free and there is an increasing demand for the generation of training data, also with regard to machine learning, suitable annotation tools are required. This paper defines criteria of flexibility and efficiency of complex annotations for the assessment of existing annotation tools. To extend this list of tools, the paper describes TextAnnotator, a browser-based, multi-annotation system, which has been developed to perform platform-independent multimodal annotations and annotate complex textual structures. The paper illustrates the current state of development of TextAnnotator and demonstrates its ability to evaluate annotation quality (inter-annotator agreement) at runtime. In addition, it will be shown how annotations of different users can be performed simultaneously and collaboratively on the same document from different platforms using UIMA as the basis for annotation.

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Transfer of ISOSpace into a 3D Environment for Annotations and Applications
Alexander Henlein | Giuseppe Abrami | Attila Kett | Alexander Mehler
16th Joint ACL - ISO Workshop on Interoperable Semantic Annotation PROCEEDINGS

People’s visual perception is very pronounced and therefore it is usually no problem for them to describe the space around them in words. Conversely, people also have no problems imagining a concept of a described space. In recent years many efforts have been made to develop a linguistic concept for spatial and spatial-temporal relations. However, the systems have not really caught on so far, which in our opinion is due to the complex models on which they are based and the lack of available training data and automated taggers. In this paper we describe a project to support spatial annotation, which could facilitate annotation by its many functions, but also enrich it with many more information. This is to be achieved by an extension by means of a VR environment, with which spatial relations can be better visualized and connected with real objects. And we want to use the available data to develop a new state-of-the-art tagger and thus lay the foundation for future systems such as improved text understanding for Text2Scene.

2018

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A UIMA Database Interface for Managing NLP-related Text Annotations
Giuseppe Abrami | Alexander Mehler
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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TreeAnnotator: Versatile Visual Annotation of Hierarchical Text Relations
Philipp Helfrich | Elias Rieb | Giuseppe Abrami | Andy Lücking | Alexander Mehler
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)