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Animacy Detection in Stories

Authors Folgert Karsdorp, Marten van der Meulen, Theo Meder, Antal van den Bosch

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Folgert Karsdorp
Marten van der Meulen
Theo Meder
Antal van den Bosch

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Folgert Karsdorp, Marten van der Meulen, Theo Meder, and Antal van den Bosch. Animacy Detection in Stories. In 6th Workshop on Computational Models of Narrative (CMN 2015). Open Access Series in Informatics (OASIcs), Volume 45, pp. 82-97, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2015)


This paper presents a linguistically uninformed computational model for animacy classification. The model makes use of word n-grams in combination with lower dimensional word embedding representations that are learned from a web-scale corpus. We compare the model to a number of linguistically informed models that use features such as dependency tags and show competitive results. We apply our animacy classifier to a large collection of Dutch folktales to obtain a list of all characters in the stories. We then draw a semantic map of all automatically extracted characters which provides a unique entrance point to the collection.
  • animacy detection
  • word embeddings
  • folktales


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