TextAnnotator

About
In different disciplines, scholars are supported in their research by the use of digital methods to process increasingly large amounts of data. For the necessary annotation, tools are required which 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 different use cases: annotating temporal structures, argument structures, propositional structures, rhetorical structures and named entity linking.

About TextAnnotatorUsage TextAnnotator

Total: 6

2020 (2)

  • [https://dh2020.adho.org/wp-content/uploads/2020/07/547_TextAnnotatorAwebbasedannotationsuitefortexts.html] [DOI] G. Abrami, A. Mehler, and M. Stoeckel, “TextAnnotator: A web-based annotation suite for texts,” in Proceedings of the Digital Humanities 2020, 2020.
    [Abstract] [Poster][BibTeX]

    The TextAnnotator is a tool for simultaneous and collaborative annotation of texts with visual annotation support, integration of knowledge bases and, by pipelining the TextImager, a rich variety of pre-processing and automatic annotation tools. It includes a variety of modules for the annotation of texts, which contains the annotation of argumentative, rhetorical, propositional and temporal structures as well as a module for named entity linking and rapid annotation of named entities. Especially the modules for annotation of temporal, argumentative and propositional structures are currently unique in web-based annotation tools. The TextAnnotator, which allows the annotation of texts as a platform, is divided into a front- and a backend component. The backend is a web service based on WebSockets, which integrates the UIMA Database Interface to manage and use texts. Texts are made accessible by using the ResourceManager and the AuthorityManager, based on user and group access permissions. Different views of a document can be created and used depending on the scenario. Once a document has been opened, access is gained to the annotations stored within annotation views in which these are organized. Any annotation view can be assigned with access permissions and by default, each user obtains his or her own user view for every annotated document. In addition, with sufficient access permissions, all annotation views can also be used and curated. This allows the possibility to calculate an Inter-Annotator-Agreement for a document, which shows an agreement between the annotators. Annotators without sufficient rights cannot display this value so that the annotators do not influence each other. This contribution is intended to reflect the current state of development of TextAnnotator, demonstrate the possibilities of an instantaneous Inter-Annotator-Agreement and trigger a discussion about further functions for the community.
    @InProceedings{Abrami:Mehler:Stoeckel:2020,
      author         = {Abrami, Giuseppe and Mehler, Alexander and Stoeckel, Manuel},
      title          = {{TextAnnotator}: A web-based annotation suite for texts},
      booktitle      = {Proceedings of the Digital Humanities 2020},
      series         = {DH 2020},
      location       = {Ottawa, Canada},
      year           = {2020},
      url            = {https://dh2020.adho.org/wp-content/uploads/2020/07/547_TextAnnotatorAwebbasedannotationsuitefortexts.html},
      doi     = {http://dx.doi.org/10.17613/tenm-4907},
      abstract    = {The TextAnnotator is a tool for simultaneous and collaborative annotation of texts with visual annotation support, integration of knowledge bases and, by pipelining the TextImager, a rich variety of pre-processing and automatic annotation tools. It includes a variety of modules for the annotation of texts, which contains the annotation of argumentative, rhetorical, propositional and temporal structures as well as a module for named entity linking and rapid annotation of named entities. Especially the modules for annotation of temporal, argumentative and propositional structures are currently unique in web-based annotation tools. The TextAnnotator, which allows the annotation of texts as a platform, is divided into a front- and a backend component. The backend is a web service based on WebSockets, which integrates the UIMA Database Interface to manage and use texts. Texts are made accessible by using the ResourceManager and the AuthorityManager, based on user and group access permissions. Different views of a document can be created and used depending on the scenario. Once a document has been opened, access is gained to the annotations stored within annotation views in which these are organized. Any annotation view can be assigned with access permissions and by default, each user obtains his or her own user view for every annotated document. In addition, with sufficient access permissions, all annotation views can also be used and curated. This allows the possibility to calculate an Inter-Annotator-Agreement for a document, which shows an agreement between the annotators. Annotators without sufficient rights cannot display this value so that the annotators do not influence each other. This contribution is intended to reflect the current state of development of TextAnnotator, demonstrate the possibilities of an instantaneous Inter-Annotator-Agreement and trigger a discussion about further functions for the community.},
     poster     = {https://hcommons.org/deposits/download/hc:31816/CONTENT/dh2020_textannotator_poster.pdf}
    }
  • [PDF] [https://www.aclweb.org/anthology/2020.lrec-1.112] G. Abrami, M. Stoeckel, and A. Mehler, “TextAnnotator: A UIMA Based Tool for the Simultaneous and Collaborative Annotation of Texts,” in Proceedings of The 12th Language Resources and Evaluation Conference, Marseille, France, 2020, pp. 891-900.
    [Abstract] [BibTeX]

    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.
    @InProceedings{Abrami:Stoeckel:Mehler:2020,
      author    = {Abrami, Giuseppe  and  Stoeckel, Manuel  and  Mehler, Alexander},
      title     = {TextAnnotator: A UIMA Based Tool for the Simultaneous and Collaborative Annotation of Texts},
      booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
      month     = {May},
      year      = {2020},
      address   = {Marseille, France},
      publisher = {European Language Resources Association},
      pages     = {891--900},
      ISBN = "979-10-95546-34-4",
      abstract  = {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.},
      url       = {https://www.aclweb.org/anthology/2020.lrec-1.112},
      pdf       = {http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.112.pdf}
    }

2019 (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.
    [Abstract] [BibTeX]

    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.
    @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."
    }

2018 (3)

  • [PDF] G. Abrami, A. Mehler, P. Helfrich, and E. Rieb, “TextAnnotator: A Browser-based Framework for Annotating Textual Data in Digital Humanities,” in Proceedings of the Digital Humanities Austria 2018, 2018.
    [BibTeX]

    @InProceedings{Abrami:et:al:2018,
    Author = {Giuseppe Abrami and Alexander Mehler and Philipp Helfrich and Elias Rieb},
    Title = {{TextAnnotator}: A Browser-based Framework for Annotating Textual Data in Digital Humanities},
    BookTitle = {Proceedings of the Digital Humanities Austria 2018},
    pdf = {https://www.texttechnologylab.org/wp-content/uploads/2019/04/TA__A_Browser_based_Framework_for_Annotating_Textual_Data_in_Digital_Humanities.pdf},
    location = {Salzburg, Austria},
    year = 2018
    }
  • [PDF] P. Helfrich, E. Rieb, G. Abrami, A. Lücking, and A. Mehler, “TreeAnnotator: Versatile Visual Annotation of Hierarchical Text Relations,” in Proceedings of the 11th edition of the Language Resources and Evaluation Conference, May 7 – 12, Miyazaki, Japan, 2018.
    [BibTeX]

    @InProceedings{Helfrich:et:al:2018,
      Author         = {Philipp Helfrich and Elias Rieb and Giuseppe Abrami
                       and Andy L{\"u}cking and Alexander Mehler},
      Title          = {TreeAnnotator: Versatile Visual Annotation of
                       Hierarchical Text Relations},
      BookTitle      = {Proceedings of the 11th edition of the Language
                       Resources and Evaluation Conference, May 7 - 12},
      Series         = {LREC 2018},
      Address        = {Miyazaki, Japan},
      pdf            = {https://www.texttechnologylab.org/wp-content/uploads/2018/03/TreeAnnotator.pdf},
      year           = 2018
    }
  • [PDF] G. Abrami and A. Mehler, “A UIMA Database Interface for Managing NLP-related Text Annotations,” in Proceedings of the 11th edition of the Language Resources and Evaluation Conference, May 7 – 12, Miyazaki, Japan, 2018.
    [BibTeX]

    @InProceedings{Abrami:Mehler:2018,
      Author         = {Giuseppe Abrami and Alexander Mehler},
      Title          = {A UIMA Database Interface for Managing NLP-related
                       Text Annotations},
      BookTitle      = {Proceedings of the 11th edition of the Language
                       Resources and Evaluation Conference, May 7 - 12},
      Series         = {LREC 2018},
      Address        = {Miyazaki, Japan},
      pdf            = {https://www.texttechnologylab.org/wp-content/uploads/2018/03/UIMA-DI.pdf},
      year           = 2018
    }

Total: 2

2020 (1)

  • [PDF] [https://www.aclweb.org/anthology/2020.lrec-1.112] G. Abrami, M. Stoeckel, and A. Mehler, “TextAnnotator: A UIMA Based Tool for the Simultaneous and Collaborative Annotation of Texts,” in Proceedings of The 12th Language Resources and Evaluation Conference, Marseille, France, 2020, pp. 891-900.
    [Abstract] [BibTeX]

    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.
    @InProceedings{Abrami:Stoeckel:Mehler:2020,
      author    = {Abrami, Giuseppe  and  Stoeckel, Manuel  and  Mehler, Alexander},
      title     = {TextAnnotator: A UIMA Based Tool for the Simultaneous and Collaborative Annotation of Texts},
      booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
      month     = {May},
      year      = {2020},
      address   = {Marseille, France},
      publisher = {European Language Resources Association},
      pages     = {891--900},
      ISBN = "979-10-95546-34-4",
      abstract  = {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.},
      url       = {https://www.aclweb.org/anthology/2020.lrec-1.112},
      pdf       = {http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.112.pdf}
    }

2018 (1)

  • [PDF] P. Helfrich, E. Rieb, G. Abrami, A. Lücking, and A. Mehler, “TreeAnnotator: Versatile Visual Annotation of Hierarchical Text Relations,” in Proceedings of the 11th edition of the Language Resources and Evaluation Conference, May 7 – 12, Miyazaki, Japan, 2018.
    [BibTeX]

    @InProceedings{Helfrich:et:al:2018,
      Author         = {Philipp Helfrich and Elias Rieb and Giuseppe Abrami
                       and Andy L{\"u}cking and Alexander Mehler},
      Title          = {TreeAnnotator: Versatile Visual Annotation of
                       Hierarchical Text Relations},
      BookTitle      = {Proceedings of the 11th edition of the Language
                       Resources and Evaluation Conference, May 7 - 12},
      Series         = {LREC 2018},
      Address        = {Miyazaki, Japan},
      pdf            = {https://www.texttechnologylab.org/wp-content/uploads/2018/03/TreeAnnotator.pdf},
      year           = 2018
    }