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Sklepanje v naravnem jeziku s pomočjo zdravorazumske baze
ID Gospodarič, Jakob (Author), ID Robnik Šikonja, Marko (Mentor) More about this mentor... This link opens in a new window

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Abstract
V tej diplomski nalogi bomo raziskovali izboljšanje zmožnosti zdravorazumskega sklepanja jezikovnih modelov ChatGPT in SloBERTa z integracijo zdravorazumskega znanja iz baze SloATOMIC. Na začetku bomo predstavili problemsko domeno in opisali področje. Nato bomo predstavili uporabljeno tehnologijo in postopek priprave podatkov. Primerjali bomo rezultate na podatkovni bazi SI-NLI brez in z dodatnimi stavki iz SloATOMIC. Dodatno bomo še primerjali rezultate na manjši podmnožici ročno popravljenih podatkov. Na koncu bomo opisali težave in predstavili možne nadaljnje izboljšave.

Language:Slovenian
Keywords:Zdravorazumsko sklepanje, jezikovni modeli, SloATOMIC, SI-NLI, grafi znanj
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2024
PID:20.500.12556/RUL-158181 This link opens in a new window
COBISS.SI-ID:197359619 This link opens in a new window
Publication date in RUL:28.05.2024
Views:348
Downloads:63
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Secondary language

Language:English
Title:Natural language inference using commonsense reasoning database
Abstract:
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.

Keywords:Commonsense reasoning, Language models, SloATOMIC, SINLI, Knowledge graphs

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