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URN: urn:nbn:de:0030-drops-52841
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Animacy Detection in Stories

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Abstract

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.

BibTeX - Entry

@InProceedings{karsdorp_et_al:OASIcs:2015:5284,
  author =	{Folgert Karsdorp and Marten van der Meulen and Theo Meder and Antal van den Bosch},
  title =	{{Animacy Detection in Stories}},
  booktitle =	{6th Workshop on Computational Models of Narrative (CMN 2015)},
  pages =	{82--97},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-93-4},
  ISSN =	{2190-6807},
  year =	{2015},
  volume =	{45},
  editor =	{Mark A. Finlayson and Ben Miller and Antonio Lieto and Remi Ronfard},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2015/5284},
  URN =		{urn:nbn:de:0030-drops-52841},
  doi =		{10.4230/OASIcs.CMN.2015.82},
  annote =	{Keywords: animacy detection, word embeddings, folktales}
}

Keywords: animacy detection, word embeddings, folktales
Seminar: 6th Workshop on Computational Models of Narrative (CMN 2015)
Issue date: 2015
Date of publication: 2015


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