Event Detection and Classification in Hungarian Natural Texts

  • Zoltan Subecz Department of Information Technology, GAMF Faculty of Engineering and Computer Science, John von Neumann University, Hungary


The detection and analysis of events in natural language texts plays an important role in several NLP applications such as summarization and question answering. This paper focuses on introducing a machine learningbased approach that can detect and classify verbal and infinitival events in Hungarian texts. First, the multiword noun + verb and noun + infinitive expressions were identified. Then the events are detected and the identified events are classified. For each problem, binary classifiers were applied based on rich feature sets. The models were expanded with rule-based methods.


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How to Cite
Subecz, Z. (2019). Event Detection and Classification in Hungarian Natural Texts. European Scientific Journal, ESJ, 15(21), 411. https://doi.org/10.19044/esj.2019.v15n21p411