Karsdorp, Folgert
[Author];
van der Meulen, Marten
[Author];
Meder, Theo
[Author];
van den Bosch, Antal
[Author]
;
Folgert Karsdorp and Marten van der Meulen and Theo Meder and Antal van den Bosch
[Contributor]
Footnote:
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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.