• Media type: Text; Electronic Conference Proceeding; E-Article
  • Title: Animacy Detection in Stories
  • Contributor: Karsdorp, Folgert [Author]; van der Meulen, Marten [Author]; Meder, Theo [Author]; van den Bosch, Antal [Author]
  • imprint: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2015
  • Language: English
  • DOI: https://doi.org/10.4230/OASIcs.CMN.2015.82
  • Keywords: word embeddings ; animacy detection ; folktales
  • Origination:
  • Footnote: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Description: 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.
  • Access State: Open Access