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Using Sentence-Level LSTM Language Models for Script Inference

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 نشر من قبل Karl Pichotta
 تاريخ النشر 2016
  مجال البحث الهندسة المعلوماتية
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There is a small but growing body of research on statistical scripts, models of event sequences that allow probabilistic inference of implicit events from documents. These systems operate on structured verb-argument events produced by an NLP pipeline. We compare these systems with recent Recurrent Neural Net models that directly operate on raw tokens to predict sentences, finding the latter to be roughly comparable to the former in terms of predicting missing events in documents.



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