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Collaborative relation annotation and quality analysis in Markyt environment

Text mining is showing potential to help in biomedical knowledge integration and discovery at various levels. However, results depend largely on the specifics of the knowledge problem and, in particular, on the ability to produce high-quality benchmarking corpora that may support the training and ev...

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Autores principales: Pérez-Pérez, Martín, Pérez-Rodríguez, Gael, Fdez-Riverola, Florentino, Lourenço, Anália
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737204/
https://www.ncbi.nlm.nih.gov/pubmed/29220479
http://dx.doi.org/10.1093/database/bax090
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author Pérez-Pérez, Martín
Pérez-Rodríguez, Gael
Fdez-Riverola, Florentino
Lourenço, Anália
author_facet Pérez-Pérez, Martín
Pérez-Rodríguez, Gael
Fdez-Riverola, Florentino
Lourenço, Anália
author_sort Pérez-Pérez, Martín
collection PubMed
description Text mining is showing potential to help in biomedical knowledge integration and discovery at various levels. However, results depend largely on the specifics of the knowledge problem and, in particular, on the ability to produce high-quality benchmarking corpora that may support the training and evaluation of automatic prediction systems. Annotation tools enabling the flexible and customizable production of such corpora are thus pivotal. The open-source Markyt annotation environment brings together the latest web technologies to offer a wide range of annotation capabilities in a domain-agnostic way. It enables the management of multi-user and multi-round annotation projects, including inter-annotator agreement and consensus assessments. Also, Markyt supports the description of entity and relation annotation guidelines on a project basis, being flexible to partial word tagging and the occurrence of annotation overlaps. This paper describes the current release of Markyt, namely new annotation perspectives, which enable the annotation of relations among entities, and enhanced analysis capabilities. Several demos, inspired by public biomedical corpora, are presented as means to better illustrate such functionalities. Markyt aims to bring together annotation capabilities of broad interest to those producing annotated corpora. Markyt demonstration projects describe 20 different annotation tasks of varied document sources (e.g. abstracts, twitters or drug labels) and languages (e.g. English, Spanish or Chinese). Continuous development is based on feedback from practical applications as well as community reports on short- and medium-term mining challenges. Markyt is freely available for non-commercial use at http://markyt.org. Database URL: http://markyt.org
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spelling pubmed-57372042018-01-05 Collaborative relation annotation and quality analysis in Markyt environment Pérez-Pérez, Martín Pérez-Rodríguez, Gael Fdez-Riverola, Florentino Lourenço, Anália Database (Oxford) Original Article Text mining is showing potential to help in biomedical knowledge integration and discovery at various levels. However, results depend largely on the specifics of the knowledge problem and, in particular, on the ability to produce high-quality benchmarking corpora that may support the training and evaluation of automatic prediction systems. Annotation tools enabling the flexible and customizable production of such corpora are thus pivotal. The open-source Markyt annotation environment brings together the latest web technologies to offer a wide range of annotation capabilities in a domain-agnostic way. It enables the management of multi-user and multi-round annotation projects, including inter-annotator agreement and consensus assessments. Also, Markyt supports the description of entity and relation annotation guidelines on a project basis, being flexible to partial word tagging and the occurrence of annotation overlaps. This paper describes the current release of Markyt, namely new annotation perspectives, which enable the annotation of relations among entities, and enhanced analysis capabilities. Several demos, inspired by public biomedical corpora, are presented as means to better illustrate such functionalities. Markyt aims to bring together annotation capabilities of broad interest to those producing annotated corpora. Markyt demonstration projects describe 20 different annotation tasks of varied document sources (e.g. abstracts, twitters or drug labels) and languages (e.g. English, Spanish or Chinese). Continuous development is based on feedback from practical applications as well as community reports on short- and medium-term mining challenges. Markyt is freely available for non-commercial use at http://markyt.org. Database URL: http://markyt.org Oxford University Press 2017-12-05 /pmc/articles/PMC5737204/ /pubmed/29220479 http://dx.doi.org/10.1093/database/bax090 Text en © The Author(s) 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Pérez-Pérez, Martín
Pérez-Rodríguez, Gael
Fdez-Riverola, Florentino
Lourenço, Anália
Collaborative relation annotation and quality analysis in Markyt environment
title Collaborative relation annotation and quality analysis in Markyt environment
title_full Collaborative relation annotation and quality analysis in Markyt environment
title_fullStr Collaborative relation annotation and quality analysis in Markyt environment
title_full_unstemmed Collaborative relation annotation and quality analysis in Markyt environment
title_short Collaborative relation annotation and quality analysis in Markyt environment
title_sort collaborative relation annotation and quality analysis in markyt environment
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737204/
https://www.ncbi.nlm.nih.gov/pubmed/29220479
http://dx.doi.org/10.1093/database/bax090
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