Abstract
In this short paper, we discuss a straight-forward approach for the identification of noun phrases denoting actors (agents). We use a multilayer perceptron applied to the word embeddings of the head nouns in order to learn a model. A list of 9,000 actors together with 11,000 non-actors generated from a newspaper corpus are used as a silver standard. An evaluation of the results seems to indicate that the model generalises well on unseen data.