| Abstract | The proposed models are tested on three different tasks: coarse-grained word sense disambiguation, fine-grained word sense disambiguation, and detection of literal vs. nonliteral usages of potentially idiomatic expressions. |
| Conclusion | We test the proposed models on three tasks. |
| Experiments | Table 5 shows the results of our proposed model compared with state-of-the-art systems. |
| The Sense Disambiguation Model | To overcome this problem, we propose Model 11, which indirectly maximizes the sense-context probability by maximizing the cosine value of two document vectors that encode the document-topic frequencies from sampling, v(z|dc) and v(z|ds). |
| The Sense Disambiguation Model | We propose Model III: |