In this thesis, we will explore the enhancement of the commonsense reasoning
capabilities of the language models ChatGPT and SloBERTa by integrating
commonsense knowledge from the SloATOMIC database. We will begin by
presenting the problem domain and describing the field. Then, we will introduce
the technology used and the data preparation process. We will compare
the results on the SI-NLI dataset with and without the additional sentences
from SloATOMIC. Additionally, we will compare the results on a smaller
subset of manually corrected data. Finally, we will describe the challenges
encountered and present possible further improvements.
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