Definition extraction with balanced Random Forests

We propose a novel machine learning approach to the task of identifying definitions in Polish documents. Specifics of the problem domain and characteristics of the available dataset have been taken into consideration, by carefully choosing and adapting a classification method to highly imbalanced and noisy data. We evaluate the performance of a Random Forest-based classifier in extracting definitional sentences from natural language text and give a comparison with previous work.