A simpler and more generalizable story detector using verb and character features Conference

Eisenberg, JD, Finlayson, MA. (2017). A simpler and more generalizable story detector using verb and character features . 2708-2715. 10.18653/v1/d17-1287

cited authors

  • Eisenberg, JD; Finlayson, MA

fiu authors

abstract

  • Story detection is the task of determining whether or not a unit of text contains a story. Prior approaches achieved a maximum performance of 0.66 F1, and did not generalize well across different corpora. We present a new state-of-the-art detector that achieves a maximum performance of 0.75 F1 (a 14% improvement), with significantly greater generalizability than previous work. In particular, our detector achieves performance above 0.70 F1 across a variety of combinations of lexically different corpora for training and testing, as well as dramatic improvements (up to 4,000%) in performance when trained on a small, disfluent data set. The new detector uses two basic types of features–ones related to events, and ones related to characters–totaling 283 specific features overall; previous detectors used tens of thousands of features, and so this detector represents a significant simplification along with increased performance.

publication date

  • January 1, 2017

Digital Object Identifier (DOI)

International Standard Book Number (ISBN) 13

  • 9781945626838

start page

  • 2708

end page

  • 2715