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- W2964102772 abstract "Modal sense classification (MSC) is a special WSD task that depends on the meaning of the proposition in the modal's scope. We explore a CNN architecture for classifying modal sense in English and German. We show that CNNs are superior to manually designed feature-based classifiers and a standard NN classifier. We analyze the feature maps learned by the CNN and identify known and previously unattested linguistic features. We benchmark the CNN on a standard WSD task, where it compares favorably to models using sense-disambiguated target vectors." @default.
- W2964102772 created "2019-07-30" @default.
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- W2964102772 date "2016-01-01" @default.
- W2964102772 modified "2023-09-26" @default.
- W2964102772 title "Multilingual Modal Sense Classification using a Convolutional Neural Network" @default.
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- W2964102772 doi "https://doi.org/10.18653/v1/w16-1613" @default.
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