Kristian Martiskainen


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Automated Emotion Annotation of Finnish Parliamentary Speeches Using GPT-4
Otto Tarkka | Jaakko Koljonen | Markus Korhonen | Juuso Laine | Kristian Martiskainen | Kimmo Elo | Veronika Laippala
Proceedings of the IV Workshop on Creating, Analysing, and Increasing Accessibility of Parliamentary Corpora (ParlaCLARIN) @ LREC-COLING 2024

In this paper, we test the efficacy of using GPT-4 to annotate a dataset that is the used to train a BERT classifier for emotion analysis. Manual data annotation is often a laborious and expensive task and emotion annotation, specifically, has proved difficult even for expert annotators. We show that using GPT-4 can produce equally good results as doing data annotation manually while saving a lot of time and money. We train a BERT classifier on our automatically annotated dataset and get results that outperform a BERT classifier that is trained on machine translated data. Our paper shows how Large Language Models can be used to work with and analyse parliamentary corpora.