Prompt-Based Approach for Czech Sentiment Analysis
Jakub Šmíd, Pavel Přibáň · 2023
This paper introduces the first prompt-based methods for aspect-based sentiment analysis and sentiment classification in Czech.We employ the sequence-to-sequence models to solve the aspect-based tasks simultaneously and demonstrate the superiority of our promptbased approach over traditional fine-tuning.In addition, we conduct zero-shot and few-shot learning experiments for sentiment classification and show that prompting yields significantly better results with limited training examples compared to traditional fine-tuning.We also demonstrate that pre-training on data from the target domain can lead to significant improvements in a zero-shot scenario.