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Title: Towards cross-platform interoperability for machine-assisted annotation
In this paper we investigate cross-platform interoperability for natural language processing (NLP) and, in particular, annota- tion 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 seam- less 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 con- sider 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.  more » « less
Award ID(s):
1811123
PAR ID:
10096184
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Genomics & Informatics
Volume:
17
Issue:
2
ISSN:
1598-866X
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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