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Towards cross-platform interoperability for machine-assisted annotation

Eckart de Castilho, Richard and Ide, Nancy and Kim, Jin-Dong and Klie, Jan-Christoph and Suderman, Keith (2019):
Towards cross-platform interoperability for machine-assisted annotation.
In: Genomics & Informatics, Genomics Inform, pp. e19., 17, (2), DOI: 10.5808/GI.2019.17.2.e19,
[Online-Edition: https://genominfo.org/journal/view.php?number=560],
[Article]

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Abstract

In this paper, we investigate cross-platform interoperability for natural language processing (NLP) and, in particular, annotation of textual resources, with an eye toward identifying the design elements of annotation models and processes that are particularly problematic for, or amenable to, enabling seamless communication across different platforms. The study is conducted in the context of a specific annotation methodology, namely machine-assisted interactive annotation (also known as human-in-the-loop annotation). This methodology requires the ability to freely combine resources from different document repositories, access a wide array of NLP tools that automatically annotate corpora for various linguistic phenomena, and use a sophisticated annotation editor that enables interactive manual annotation coupled with on-the-fly machine learning. We consider three independently developed platforms, each of which utilizes a different model for representing annotations over text, and each of which performs a different role in the process.

Item Type: Article
Erschienen: 2019
Creators: Eckart de Castilho, Richard and Ide, Nancy and Kim, Jin-Dong and Klie, Jan-Christoph and Suderman, Keith
Title: Towards cross-platform interoperability for machine-assisted annotation
Language: English
Abstract:

In this paper, we investigate cross-platform interoperability for natural language processing (NLP) and, in particular, annotation of textual resources, with an eye toward identifying the design elements of annotation models and processes that are particularly problematic for, or amenable to, enabling seamless communication across different platforms. The study is conducted in the context of a specific annotation methodology, namely machine-assisted interactive annotation (also known as human-in-the-loop annotation). This methodology requires the ability to freely combine resources from different document repositories, access a wide array of NLP tools that automatically annotate corpora for various linguistic phenomena, and use a sophisticated annotation editor that enables interactive manual annotation coupled with on-the-fly machine learning. We consider three independently developed platforms, each of which utilizes a different model for representing annotations over text, and each of which performs a different role in the process.

Journal or Publication Title: Genomics & Informatics
Volume: 17
Number: 2
Publisher: Genomics Inform
Uncontrolled Keywords: UKP_p_INCEpTION
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
Date Deposited: 01 Jul 2019 09:06
DOI: 10.5808/GI.2019.17.2.e19
Official URL: https://genominfo.org/journal/view.php?number=560
Projects: UKP_p_INCEpTION
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