Detection and Classification of Events in Hungarian Natural Language Texts

摘要

The detection and analysis of events in natural language texts plays an important role in several NLP applications such as summarization and question answering. In this study we introduce a machine learning-based approach that can detect and classify verbal and infinitival events in Hungarian texts. First we identify the multiword noun + verb and noun + infinitive expressions. Then the events are detected and the identified events are classified. For each problem, we applied binary classifiers based on rich feature sets. The models were expanded with rule-based methods too. In this study we introduce new methods for this application area. According to our best knowledge ours is the first result for detection and classification of verbal and infinitival events in Hungarian natural language texts. Evaluating them on test databases, our algorithms achieved competitive results as compared to the current English results.