The meaning of such verb-noun combinations as take care, undertake work, pay attention can be generalized as DO what is designated by the noun. Likewise, the meaning of make a decision, provide support, write a letter can be generalized as MAKE what is designated by the noun. These generalizations represent the meaning of certain groups of verb-noun combinations. We use supervised machine learning algorithms to predict the meanings DO, MAKE, BEGIN, and CONTINUE of previously unseen verbnoun pairs. We evaluate the performance of the applied algorithms on a training set using 10-fold cross-validation technique. The learnt models have also been evaluated on an independent test set and the predictions have been checked manually to determine the accuracy of the classifiers. The obtained results show that supervised machine learning methods achieve significant accuracy and can be used for semantic annotation of verb-noun combinations.
Olga Kolesnikova, Alexander F. Gelbukh