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Clinical TempEval 2016 evaluated temporal information extraction systems on the clinical domain. Nine sub-tasks were included, covering problems in time expression identification, event expression identification and temporal relation identification. Participant systems were trained and evaluated on a corpus of clinical and pathology notes from the Mayo(More)
In this paper, we propose a lexical senses representation system called E-HowNet, in which the lexical senses are defined by basic concepts. As a result, the meanings of expressions are more specific than those derived by using primitives. We also design an ontology to express the taxo-nomic relations between concepts and the attributes of concepts. To(More)
This research describes the development of a supervised classifier of English light verb constructions, for example , take a walk and make a speech. This classifier relies on features from dependency parses, OntoNotes sense tags, WordNet hypernyms and WordNet lexical file information. Evaluation shows that this system achieves an 89% F1 score (four points(More)
In this paper, we introduce an Abstract Meaning Representation (AMR) to Dependency Parse aligner. Alignment is a preliminary step for AMR parsing, and our aligner improves current AMR parser performance. Our aligner involves several different features, including named entity tags and semantic role labels, and uses Expectation-Maximization training. Results(More)
Thrips-borne tospoviruses cause numerous plant diseases that produce severe economic losses worldwide. In the disease system, thrips not only damage plants through feeding but also transmit causative agents of epidemics. In addition, thrips are infected with tospoviruses in the course of virus transmission. Most studies on the effect of tospoviruses on(More)
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