Abstract: We present a data-driven technique for acquiring domain-level importance of verbs from the analysis of abstract/article pairs of world news articles. We show that existing lexical resources capture some the semantic characteristics for important words in the domain. We develop a novel characterization of the association between verbs and personal story narratives, which is descriptive of verbs avoided in summaries for this domain.
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