Sylvia Springorum

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The current study works at the interface of theoretical and computational linguistics to explore the semantic properties of an particle verbs, i.e., German particle verbs with the particle an. Based on a thorough analysis of the particle verbs from a theoretical point of view, we identified empirical features and performed an automatic semantic(More)
For many NLP applications such as Information Extraction and Sentiment Detection , it is of vital importance to distinguish between synonyms and antonyms. While the general assumption is that dis-tributional models are not suitable for this task, we demonstrate that using suitable features, differences in the contexts of synonymous and antonymous German(More)
This paper presents a methodology to identify polysemous German prepositions by exploring their vector spatial properties. We apply two cluster evaluation metrics (the Silhouette Value (Kaufman and Rousseeuw, 1990) and a fuzzy version of the V-Measure (Rosenberg and Hirschberg, 2007)) as well as various correlations , to exploit hard vs. soft cluster(More)
This paper provides a corpus-based study on German particle verbs. We hypothesize that there are regular mechanisms in meaning shifts of a base verb in combination with a particle that do not only apply to the individual verb, but across a semantically coherent set of verbs. For example, the syntactically similar base verbs brummen 'hum' and donnern(More)
Measure for comparison of two completely independent clusterings with no restrictions in their similarity, the number of data points, or the number of clusters. → A weighted harmonic mean of homogeneity and completeness values. Homogeneity Measure of how homogeneous the clusters in the clustering are Completeness Measure of how intact the gold standard(More)
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(More)
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