GATE Teamware: a web-based, collaborative text annotation framework

Bontcheva, Kalina; Cunningham, Hamish; Roberts, Ian; Roberts, Angus; Tablan, Valentin; Aswani, Niraj; Gorrell, Genevieve

doi:10.1007/s10579-013-9215-6

Cited by 89 publications

(57 citation statements)

References 10 publications

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“…TimeLineCurator [23] automatically extracts temporal events from unstructured text data and enables users to curate them in a visual, annotated timeline. Bontcheva et al [6] have presented a collaborative text annotation framework and emphasize the importance of pre-annotation to significantly reduce annotation costs. Skeppstedt et al have presented a framework that creates BRAT-compatible pre-annotations [57] and discuss (dis-)advantages of preannotation.…”

Section: Related Workmentioning

confidence: 99%

VIANA: Visual Interactive Annotation of Argumentation

Sperrle

Sevastjanova

Kehlbeck

et al. 2019

2019 IEEE Conference on Visual Analytics Science and Technology (VAST)

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Figure 1: VIANA is a system for interactive annotation of argumentation. It offers five different analysis layers, each represented by a different view and tailored to a specific task. The layers are connected with semantic transitions. With increasing progress of the analysis, users can abstract away from the text representation and seamlessly transition towards distant reading interfaces. ABSTRACTArgumentation Mining addresses the challenging tasks of identifying boundaries of argumentative text fragments and extracting their relationships. Fully automated solutions do not reach satisfactory accuracy due to their insufficient incorporation of semantics and domain knowledge. Therefore, experts currently rely on time-consuming manual annotations. In this paper, we present a visual analytics system that augments the manual annotation process by automatically suggesting which text fragments to annotate next. The accuracy of those suggestions is improved over time by incorporating linguistic knowledge and language modeling to learn a measure of argument similarity from user interactions. Based on a long-term collaboration with domain experts, we identify and model five high-level analysis tasks. We enable close reading and note-taking, annotation of arguments, argument reconstruction, extraction of argument relations, and exploration of argument graphs. To avoid context switches, we transition between all views through seamless morphing, visually anchoring all text-and graph-based layers. We evaluate our system with a two-stage expert user study based on a corpus of presidential debates. The results show that experts prefer our system over existing solutions due to the speedup provided by the automatic suggestions and the tight integration between text and graph views.

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Section: Related Workmentioning

confidence: 99%

VIANA: Visual Interactive Annotation of Argumentation

Sperrle

Sevastjanova

Kehlbeck

et al. 2019

2019 IEEE Conference on Visual Analytics Science and Technology (VAST)

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“…We considered several other possible annotation tools for our project, such as MMAX2 (Müller and Strube, 2006), GATE Teamware (Bontcheva et al, 2013) and Arethusa 4 . The main reasons for se-lecting BRAT as tool for the implementation of our annotation scheme were its web interface and its flexibility: BRAT accommodates the annotation of discontinuous spans as one entity and supports different types of relations and attributes.…”

Section: Brat Rapid Annotation Toolmentioning

confidence: 99%

Annotating Speech, Attitude and Perception Reports

Bary

Hess

Thijs³

et al. 2017

Proceedings of the 11th Linguistic Annotation Workshop

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We present REPORTS, an annotation scheme for the annotation of speech, attitude and perception reports. The scheme makes it possible to annotate the various text elements involved in such reports (e.g. embedding entity, complement, complement head) and their relations in a uniform way, which in turn facilitates the automatic extraction of information on, for example, complementation and vocabulary distribution. We also present the Ancient Greek corpus RAG (Thucydides' History of the Peloponnesian War), to which we have applied this scheme using the annotation tool BRAT. We discuss some of the issues, both theoretical and practical, that we encountered, show how the corpus helps in answering specific questions about narrative perspective and the relation between report type and complement type, and conclude that REPORTS fitted in well with our needs.

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“…Indeed, WebProtégé [30] is an extension of the Protégé ontology editor that allows the ontology engineering process to be performed by a larger, distributed group of contributors. Similarly, in the area of natural language processing, GATE Teamware extends the GATE linguistic annotation toolkit with distributed knowledge creation capabilities [1]. While these extensions support the collaborative and distributed work of knowledge experts (ontology engineers and linguists), recent approaches have tried further broadening this process by allowing large populations of non-experts to create knowledge through the use of crowdsourcing techniques such as games or mechanised labour platforms.…”

Section: Introductionmentioning

confidence: 99%

Crowd-based ontology engineering with the uComp Protégé plugin

Wohlgenannt

Sabou

Hanika

2016

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Abstract. Crowdsourcing techniques provide effective means for solving a variety of ontology engineering problems. Yet, they are mainly used as external support to ontology engineering, without being closely integrated into the work of ontology engineers. In this paper we investigate how to closely integrate crowdsourcing into ontology engineering practices. Firstly, we show that a set of basic crowdsourcing tasks are used recurrently to solve a range of ontology engineering problems. Secondly, we present the uComp Protégé plugin that facilitates the integration of such typical crowdsourcing tasks into ontology engineering from within the Protégé ontology editor. An evaluation of the plugin in a typical ontology engineering scenario where ontologies are built from automatically learned semantic structures, shows that its use reduces the working times for the ontology engineers 11 times, lowers the overall task costs by 40% to 83% depending on the crowdsourcing settings used and leads to data quality comparable with that of tasks performed by ontology engineers. Evaluations on a large anatomy ontology confirm that crowdsourcing is a scalable and effective method: good quality results (accuracy of 89% and 99%) are obtained while achieving cost reductions of 75% from the ontology engineer costs and providing comparable overall task duration.

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GATE Teamware: a web-based, collaborative text annotation framework

Cited by 89 publications

References 10 publications

VIANA: Visual Interactive Annotation of Argumentation

VIANA: Visual Interactive Annotation of Argumentation

Annotating Speech, Attitude and Perception Reports

Crowd-based ontology engineering with the uComp Protégé plugin

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