Paper ID: 2306.07636

Hybrid lemmatization in HuSpaCy

Péter Berkecz, György Orosz, Zsolt Szántó, Gergő Szabó, Richárd Farkas

Lemmatization is still not a trivial task for morphologically rich languages. Previous studies showed that hybrid architectures usually work better for these languages and can yield great results. This paper presents a hybrid lemmatizer utilizing both a neural model, dictionaries and hand-crafted rules. We introduce a hybrid architecture along with empirical results on a widely used Hungarian dataset. The presented methods are published as three HuSpaCy models.

Submitted: Jun 13, 2023