Work

Exploring ways beyond the simple supervised learning approach for biological event extraction

Year: 2009

Type: conference-paper

Abstract: Our paper presents the comparison of a machine-learnt and a manually constructed expert-rule-based biological event extraction system and some preliminary experiments to apply a negation and speculation detection system to further classify the extracted events. We report results on the BioNLP'09 Shared Task on Event Extraction evaluation datasets, and also on an external dataset for negation and speculation detection.

DOI: 10.3115/1572340.1572363

Authors: György Móra, Richárd Farkas, György Szarvas, Zsolt Molnár

Institutions: MTA-SZTE Research Group on Artificial Intelligence, Technische Universität Darmstadt

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Funders: Nemzeti Kutatási és Technológiai Hivatal, Magyarország Kormánya

OpenAlex ID: W1995672001

FWCI: 6.992

Cites: 6

Cited by: 16

Related to: 10