This study explores the application of Large Language Models (LLMs) to verb subcategorization in Italian, focusing on the identification and classification of syntactic patterns in sentences. While LLMs have made lexical analysis more implicit, explicit argument structure identification remains crucial in domain-specific contexts. The research leverages T-PAS, a rich lexical resource for Italian verbs, to fine-tune the open multilingual model Mistral 7B using the Iterative Reasoning Preference Optimization (IRPO) technique. This approach aims to enhance the recognition and extraction of verbal patterns from Italian sentences, addressing challenges in resource quality, coverage, and frame extraction methods. By combining curated lexical-semantic resources with neural language models, this work contributes to improving verb subcategorization tasks, particularly for the Italian language, and demonstrates the potential of LLMs in refining linguistic analysis tools.

This paper reports on research activities on automatic methods for the enrichment of the Senso Comune platform. At this stage of development, we will report on two tasks, namely word sense alignment with MultiWordNet and automatic acquisition of Verb Shallow Frames from sense annotated data in the MultiSemCor corpus. The results obtained are satisfying. We achieved a final F-measure of 0.64 for noun sense alignment and a F-measure of 0.47 for verb sense alignment, and an accuracy of 68% on the acquisition of Verb Shallow Frames.

This paper introduces the general features of Senso Comune, an open knowledge base for the Italian language, focusing on the interplay of lexical and ontological knowledge, and outlining our approach to conceptual knowledge elicitation. Senso Comune consists of a machine-readable lexicon constrained by an ontological infrastructure. The idea at the basis of Senso Comune is that natural languages exist in use, and they belong to their users. In the line of Saussure's linguistics, natural languages are seen as a social product and their main strength relies on the users’ consensus. At the same time, language has specific goals: i.e. referring to entities that belong to the users’ world (be it physical or not) and that are made up in social environments where expressions are produced and understood. This usage leverages the creativity of those who produce words and try to understand them. This is the reason why ontology, i.e. a shared conceptualization of the world, can be regarded to as the soil on which the speakers' consensus may be rooted. Some final remarks concerning future work and applications are also given.