Papers by Maximilian Köper
Combining Abstractness and Language-specific Theoretical Indicators for Detecting Non-Literal Usage of Estonian Particle Verbs (N18-4)
Copied to clipboard
| Challenge: | Existing studies on identifying nonliteral language use have focused on resource-rich languages and focused on general indicators to identify non-literal meaning. |
| Approach: | They propose to use two datasets and a random forest classifier to automatically predict literal vs. non-literal language usage for a highly frequent type of multi-word expression in a low-resource language, i.e., Estonian. |
| Outcome: | The proposed dataset outperforms a high majority baseline when combined with language-independent features of non-literal language. |
Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models (N18-2)
Copied to clipboard
| Challenge: | German particle verbs are complex verb structures that combine a prefix particle with a base verb. |
| Approach: | They propose a computational model to detect and distinguish analogies in meaning shifts between German base and complex verbs using a standard similarity model. |
| Outcome: | The proposed model detects and distinguishes analogies in meaning shifts between German base and complex verbs using a standard similarity model. |