Refine
Year of publication
- 2014 (1)
Document Type
Language
- English (1)
Has Fulltext
- yes (1)
Is part of the Bibliography
- no (1)
Keywords
- Computerlinguistik (1)
- Opinion Mining (1)
- Sentiment Analyse (1)
- Sentiment Analysis (1)
Institute
German Perception Verbs: Automatic Classification of Prototypical and Multiple Non-literal Meanings
(2014)
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.
