Redcoat: A Collaborative Annotation Tool for Hierarchical Entity Typing

Research output: Chapter in Book/Conference paperConference paper

Abstract

We introduce Redcoat, a web-based annotation tool that supports collaborative hierarchical entity typing. As an annotation tool, Redcoat also facilitates knowledge elicitation by allowing the creation and continuous refinement of concept hierarchies during annotation. It aims to minimise not only annotation time but the time it takes for project creators to set up and distribute projects to annotators. Projects created using the web-based interface can be rapidly distributed to a list of email addresses. Redcoat handles the propagation of documents amongst annotators and automatically scales the annotation workload depending on the number of active annotators. In this paper we discuss these key features and outline Redcoat’s system architecture. We also highlight Redcoat’s unique benefits over existing annotation tools via a qualitative comparison.
Original languageEnglish
Title of host publicationProceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations
Place of PublicationUSA
PublisherAssociation for Computational Linguistics
Pages193-198
Number of pages5
ISBN (Electronic)978-1-950737-92-5
DOIs
Publication statusPublished - Nov 2019
EventThe 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing - , Hong Kong
Duration: 3 Nov 20197 Nov 2019

Conference

ConferenceThe 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing
CountryHong Kong
Period3/11/197/11/19

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Stewart, M., Liu, W., & Cardell-Oliver, R. (2019). Redcoat: A Collaborative Annotation Tool for Hierarchical Entity Typing. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations (pp. 193-198). USA: Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-3033