Towards cross-platform interoperability for machine-assisted text annotation
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, enabli...
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| Format: | Article |
| Language: | English |
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BioMed Central
2019-06-01
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| Series: | Genomics & Informatics |
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| Online Access: | http://genominfo.org/upload/pdf/gi-2019-17-2-e19.pdf |
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| author | Richard Eckart de Castilho Nancy Ide Jin-Dong Kim Jan-Christoph Klie Keith Suderman |
| author_facet | Richard Eckart de Castilho Nancy Ide Jin-Dong Kim Jan-Christoph Klie Keith Suderman |
| author_sort | Richard Eckart de Castilho |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-5d51f3e4eee74d9fa6cb0c33d56b9945 |
| institution | Kabale University |
| issn | 2234-0742 |
| language | English |
| publishDate | 2019-06-01 |
| publisher | BioMed Central |
| record_format | Article |
| series | Genomics & Informatics |
| spelling | doaj-art-5d51f3e4eee74d9fa6cb0c33d56b99452025-02-02T20:01:07ZengBioMed CentralGenomics & Informatics2234-07422019-06-0117210.5808/GI.2019.17.2.e19560Towards cross-platform interoperability for machine-assisted text annotationRichard Eckart de Castilho0Nancy Ide1Jin-Dong Kim2Jan-Christoph Klie3Keith Suderman4 UKP Lab, Technical University Darmstadt, 64289 Darmstadt, Germany Vassar College, Poughkeepsie, NY 12604-0520, USA Database Center for Life Science, Research Organization of Information and Systems, Kashiwa 277-0871, Japan UKP Lab, Technical University Darmstadt, 64289 Darmstadt, Germany Vassar College, Poughkeepsie, NY 12604-0520, USAIn 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.http://genominfo.org/upload/pdf/gi-2019-17-2-e19.pdfannotation softwarebiomedical text mininginteroperability |
| spellingShingle | Richard Eckart de Castilho Nancy Ide Jin-Dong Kim Jan-Christoph Klie Keith Suderman Towards cross-platform interoperability for machine-assisted text annotation Genomics & Informatics annotation software biomedical text mining interoperability |
| title | Towards cross-platform interoperability for machine-assisted text annotation |
| title_full | Towards cross-platform interoperability for machine-assisted text annotation |
| title_fullStr | Towards cross-platform interoperability for machine-assisted text annotation |
| title_full_unstemmed | Towards cross-platform interoperability for machine-assisted text annotation |
| title_short | Towards cross-platform interoperability for machine-assisted text annotation |
| title_sort | towards cross platform interoperability for machine assisted text annotation |
| topic | annotation software biomedical text mining interoperability |
| url | http://genominfo.org/upload/pdf/gi-2019-17-2-e19.pdf |
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