NEOIT5 is a web application that allows users to interact with an Encoder-Decoder Language Models trained across three lexical tasks. In Reverse Dictionary, the system generates candidate words from natural-language definitions, optionally guided by part-of-speech constraints, semantic labels, or etymological hints. Definition Modeling enables users to generate multiple dictionary-style definitions for a given word through stochastic sampling strategies, while Exemplification Modeling produces contextual usage examples that illustrate how a word can be employed in real linguistic settings.

The demo includes two operational modes: one focused on attested lexical items, ensuring outputs correspond to existing Italian words, and another dedicated to neologism exploration, allowing users to investigate novel lexical candidates generated by the model. Additional parameters such as semantic tags, usage contexts, and prompt constraints provide fine-grained control over the generation process, supporting both exploratory and research-oriented use cases.

NeoIT5-large builds upon the IT5-large model and has been fine-tuned on a corpus of Italian lexical tasks derived from dictionaries and Wikipedia. The model is openly available on Hugging Face (snizio/NeoIT5-large), reflecting a commitment to reproducibility and open research practices.

With NEOIT5, we aim to offer both an interactive research demonstrator and a practical tool for studying lexical reasoning, creativity, and generalization in Neural Language Models, contributing to ongoing investigations into the linguistic competence of AI systems.

Click here to try the demo.

References

Ciaccio C., Miaschi A., Dell’Orletta F. (2025) “Evaluating Lexical Proficiency in Neural Language Models”. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), July 27–August 1st, 2025, Vienna

(Please cite the papers above if you use NEOIT5 in your research)