Abstract
This paper describes a conceptual framework that enables online NLP pipelined applications to solve various interoperability issues and data exchange problems between tools and platforms; e.g., tokenizers and part-of-speech taggers from GATE, UIMA, or other platforms. We propose a restful wrapping solution, which allows for universal resource identification for data management, a unified interface for data exchange, and a light-weight serialization for data visualization. In addition, we propose a semantic mapping-based pipeline composition, which allows experts to interactively exchange data between heterogeneous components.
Cite
CITATION STYLE
Shi, C., Verhagen, M., & Pustejovsky, J. (2014). A Conceptual Framework of Online Natural Language Processing Pipeline Application. In Proceedings of the Workshop on Open Infrastructures and Analysis Frameworks for HLT, OIAF4HLT 2014 - Held at the 25th International Conference on Computational Linguistics, COLING 2014 (pp. 53–59). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/w14-5206
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