Nhung T. H. Nguyen

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This paper describes our event extraction system that participated in the bacteria biotopes task in BioNLP Shared Task 2011. The system performs semi-supervised named entity recognition by leveraging additional information derived from external resources including a large amount of raw text. We also perform coreference resolution to deal with events having(More)
In this paper, we propose an open information extraction (Open IE) system, which attempts to extract relations (or facts) of any type from biomedical literature. What distinguishes our system from existing Open IE systems is that it uses predicate-argument structure patterns to detect the candidates of possible biomedical facts. We have manually evaluated(More)
Relation extraction is a fundamental technology in biomedical text mining. Most of the previous studies on relation extraction from biomedical literature have focused on specific or predefined types of relations, which inherently limits the types of the extracted relations. With the aim of fully leveraging the knowledge described in the literature, we(More)
Beta-galactosidase (EC 3.2.1.23), a commercially important enzyme, catalyses the hydrolysis of β-1,3- and β-1,4-galactosyl bonds of polymer or oligosaccharidesas well as transglycosylation of β-galactopyranosides. Due to catalytic properties; β-galactosidase might be useful in the milk industry to hydrolyze lactose and produce prebiotic GOS. The purpose of(More)
Many text mining applications in the biomedical domain benefit from automatic clustering of relational phrases into synonymous groups, since it alleviates the problem of spurious mismatches caused by the diversity of natural language expressions. Most of the previous work that has addressed this task of synonymy resolution uses similarity metrics between(More)
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