Many industrial NLP applications emphasise the processing and detection of nouns, especially proper nouns (Named Entity Recognition, NER). However, processing of verbs has been neglected. This project addresses that gap.
Many industrial NLP applications emphasize the processing and detection of nouns, especially proper nouns (Named Entity Recognition, NER). However, the processing of verbs has been neglected in recent years, even though it is crucial for the development of full Natural Language Understanding (NLU) systems, e.g., for the detection of intents in spoken language utterances or events in written language news articles. The META-O-NLU microproject focuses on proving the feasibility of a multilingual event-type ontology based on classes of synonymous verb senses, complemented with semantic roles and links to existing semantic lexicons. Such an ontology shall be usable for content- and knowledge-based annotation, which in turn shall allow for developing NLU parsers/analyzers. This micro-project extended the existing Czech-English SynSemClass lexicon (which displays all the necessary features, but only for two languages) by German and Polish, as a first step to show it can be extended to other languages as well.
This Humane-AI-Net micro-project was carried out by Charles University Prague (CU, Jan Hajič) and German Research Centre for Artificial Intelligence (DFKI, Georg Rehm), with Zdeňka Urešová, Karolina Zaczynska, Peter Bourgonje, and Eva Fučíková as team members.