Disambiguation between eventive and non-eventive meaning of nouns

Event extraction is an advanced form of text mining having numerous applications. One of the challenges faced by event extraction systems is the problem of automatic distinguishing between eventive and non-eventive use of ambiguous event nominals. The proposed disambiguation method relies on an automatically generated training set. In order to learn the difference between eventive and non-eventive reading of a target ambiguous nominal, the classifier is trained on two sets of automatically labelled examples featuring unambiguous distributionally similar lexical substitutes for either reading. The method was evaluated on a small sample of 6 ambiguous event-denoting nouns and performed fairly well (77,38% average accuracy, although with more than 20 individual nouns). Suggestions for future work include development of a more advanced distributional model and research towards automated selection of unambiguous substitutes.