Animacy Detection in Stories

F.B. Karsdorp, Marten van der Meulen, Theo Meder, Antal van den Bosch

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Samenvatting

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.
Originele taal-2Engels
TitelProceedings of the Workshop on Computational Models of Narrative (CMN’15)
RedacteurenMark Finlayson, Ben Miller, Antonio Lieto, Remi Ronfard
Plaats van productieAtlanta
Pagina's82-97
Aantal pagina's15
DOI's
StatusGepubliceerd - mei 2015

Publicatie series

NaamOpenAccess Series in Informatics
UitgeverijOASICS Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl Publishing, Germany

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