Sylvia Springorum


2018

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Assessing Meaning Components in German Complex Verbs: A Collection of Source-Target Domains and Directionality
Sabine Schulte im Walde | Maximilian Köper | Sylvia Springorum
Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics

This paper presents a collection to assess meaning components in German complex verbs, which frequently undergo meaning shifts. We use a novel strategy to obtain source and target domain characterisations via sentence generation rather than sentence annotation. A selection of arrows adds spatial directional information to the generated contexts. We provide a broad qualitative description of the dataset, and a series of standard classification experiments verifies the quantitative reliability of the presented resource. The setup for collecting the meaning components is applicable also to other languages, regarding complex verbs as well as other language-specific targets that involve meaning shifts.

2014

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Fuzzy V-Measure - An Evaluation Method for Cluster Analyses of Ambiguous Data
Jason Utt | Sylvia Springorum | Maximilian Köper | Sabine Schulte im Walde
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper discusses an extension of the V-measure (Rosenberg and Hirschberg, 2007), an entropy-based cluster evaluation metric. While the original work focused on evaluating hard clusterings, we introduce the Fuzzy V-measure which can be used on data that is inherently ambiguous. We perform multiple analyses varying the sizes and ambiguity rates and show that while entropy-based measures in general tend to suffer when ambiguity increases, a measure with desirable properties can be derived from these in a straightforward manner.

2013

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Regular Meaning Shifts in German Particle Verbs: A Case Study
Sylvia Springorum | Jason Utt | Sabine Schulte im Walde
Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers

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Uncovering Distributional Differences between Synonyms and Antonyms in a Word Space Model
Silke Scheible | Sabine Schulte im Walde | Sylvia Springorum
Proceedings of the Sixth International Joint Conference on Natural Language Processing

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Detecting Polysemy in Hard and Soft Cluster Analyses of German Preposition Vector Spaces
Sylvia Springorum | Sabine Schulte im Walde | Jason Utt
Proceedings of the Sixth International Joint Conference on Natural Language Processing

2012

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Automatic classification of German an particle verbs
Sylvia Springorum | Sabine Schulte im Walde | Antje Roßdeutscher
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

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 classification. A focus of the study was on the mutual profit of theoretical and empirical perspectives with respect to salient semantic properties of the an particle verbs: (a) how can we transform the theoretical insights into empirical, corpus-based features, (b) to what extent can we replicate the theoretical classification by a machine learning approach, and (c) can the computational analysis in turn deepen our insights to the semantic properties of the particle verbs? The best classification result of 70% correct class assignments was reached through a GermaNet-based generalization of direct object nouns plus a prepositional phrase feature. These particle verb features in combination with a detailed analysis of the results at the same time confirmed and enlarged our knowledge about salient properties.