Script Induction as Language Modeling

نویسندگان

  • Rachel Rudinger
  • Pushpendre Rastogi
  • Francis Ferraro
  • Benjamin Van Durme
چکیده

The narrative cloze is an evaluation metric commonly used for work on automatic script induction. While prior work in this area has focused on count-based methods from distributional semantics, such as pointwise mutual information, we argue that the narrative cloze can be productively reframed as a language modeling task. By training a discriminative language model for this task, we attain improvements of up to 27 percent over prior methods on standard narrative cloze metrics.

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تاریخ انتشار 2015