Volltext-Downloads (blau) und Frontdoor-Views (grau)

German Perception Verbs: Automatic Classification of Prototypical and Multiple Non-literal Meanings

  • This paper presents a token-based automatic classification of German perception verbs into literal vs. multiple non-literal senses. Based on a corpus-based dataset of German perception verbs and their systematic meaning shifts, we identify one verb of each of the four perception classes optical, acoustic, olfactory, haptic, and use Decision Trees relying on syntactic and semantic corpus-based features to classify the verb uses into 3-4 senses each. Our classifier reaches accuracies between 45.5% and 69.4%, in comparison to baselines between 27.5% and 39.0%. In three out of four cases analyzed our classifier’s accuracy is significantly higher than the according baseline.

Download full text files

  • Main Conference Proceedings of the 12th Konvens 2014

Export metadata

Additional Services

Share in Twitter    Search Google Scholar    frontdoor_oas
Author:Benjamin David, Sylvia Springorum, Sabine Schulte im Walde
Parent Title (English):Proceedings of the 12th edition of the KONVENS conference
Document Type:Conference Proceeding
Date of Publication (online):2014/10/23
Release Date:2014/10/23
Tag:Sentiment Analyse
Opinion Mining; Sentiment Analysis
GND Keyword:Computerlinguistik
First Page:207
Last Page:214
PPN:Link zum Katalog
Contributor:Faaß, Gertrud
Institutes:Fachbereich III / Informationswissenschaft und Sprachtechnologie
DDC classes:400 Sprache / 400 Sprache, Linguistik
Collections:KONVENS 2014 / Proceedings of the 12th KONVENS 2014
Licence (German):License LogoCreative Commons - Namensnennung 3.0