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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CITATION STYLE
Nye, B., & Nenkova, A. (2015). Identification and characterization of newsworthy verbs in world news. In NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 1440–1445). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/n15-1166
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