Multilingual Modal Sense Classification using a Convolutional Neural Network
Ana Marasović, Anette Frank · 2016
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.