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OGER: OntoGene’s Entity Recogniser in the BeCalm TIPS Task


Furrer, Lenz; Rinaldi, Fabio (2017). OGER: OntoGene’s Entity Recogniser in the BeCalm TIPS Task. In: BioCreative V.5 Challenge Evaluation Workshop, Barcelona, Spain, 26 April 2017 - 27 April 2017, 175-182.

Abstract

We present OGER, an annotation service built on top of OntoGene’s biomedical entity recognition system, which participates in the TIPS task (technical interoperability and performance of annotation servers) of the BeCalm (biomedical annotation metaserver) challenge. The annotation server is a web application tailored to the needs of the task, using an existing biomedical entity recognition suite. The core annotation module uses a knowledge-based strategy for term matching and entity linking. The server’s architecture allows parallel processing of annotation requests for an arbitrary number of documents from mixed sources. In the discussion, we show that network latency is responsible for significant overhead in the measurement of processing time. We compare the preliminary key performance indicators with an analysis drawn from the server’s log messages. We conclude that our annotation server is ready for the upcoming phases of the TIPS task.

Abstract

We present OGER, an annotation service built on top of OntoGene’s biomedical entity recognition system, which participates in the TIPS task (technical interoperability and performance of annotation servers) of the BeCalm (biomedical annotation metaserver) challenge. The annotation server is a web application tailored to the needs of the task, using an existing biomedical entity recognition suite. The core annotation module uses a knowledge-based strategy for term matching and entity linking. The server’s architecture allows parallel processing of annotation requests for an arbitrary number of documents from mixed sources. In the discussion, we show that network latency is responsible for significant overhead in the measurement of processing time. We compare the preliminary key performance indicators with an analysis drawn from the server’s log messages. We conclude that our annotation server is ready for the upcoming phases of the TIPS task.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:27 April 2017
Deposited On:08 Aug 2017 14:15
Last Modified:01 Sep 2017 09:10
Publisher:BioCreative
Funders:SNF
Official URL:http://www.biocreative.org/resources/publications/bcv5_proceedings/

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