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In this project, we have investigated the use of advanced machine learningmethods, specifically fine-tuned large language models, for pre-annotating datafor a lexical extension task, namely adding descriptive words (verbs) to anexisting (but incomplete, as of yet) ontology of event types. Several researchquestions have been focused on, from the investigation of a possible heuristicsto provide at least hints to annotators which verbs to include and which areoutside the current version of the ontology, to the possible use of theautomatic scores to help the annotators to be more efficient in finding athreshold for identifying verbs that cannot be assigned to any existing classand therefore they are to be used as seeds for a new class. We have alsocarefully examined the correlation of the automatic scores with the humanannotation. While the correlation turned out to be strong, its influence on theannotation proper is modest due to its near linearity, even though the merefact of such pre-annotation leads to relatively short annotation times.

Extending an Event-type Ontology: Adding Verbs and Classes Using Fine-tuned LLMs Suggestions