Aspectual Flexibility Increases with Agentivity and ConcretenessA Computational Classification Experiment on Polysemous Verbs
We present an experimental study making use of a machine learning approach to identify the factors that affect the aspectual value that characterizes verbs under each of their readings. The study is based on various morpho-syntactic and semantic features collected from a French lexical resource and on a gold standard aspectual classification of verb readings designed by an expert. Our results support the tested hypothesis, namely that agentivity and abstractness influence lexical aspect.
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BIG-bench Machine LearningGeneral ClassificationSimilar Papers 제목 키워드 기반
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