This report demonstrates budget argument mining accuracy in legislative contexts, indicating room for improvement.
This paper reports on the achievements of Budget Argument Mining subtask of the NTCIR-16 QA Lab-PoliInfo-3 task of fuys team. We have assigned ArgumentClass and RelatedID in different ways. ArgumentClass was assigned using BERT. We also thought that the accuracy could be improved by adding the flag indicating whether a speaker is a legislator or not ("giin-flag"). RelatedID was assigned using keyword extraction with TFIDF. The results showed good results for ArgumentClass, but the improvement in accuracy of RelatedID could not be confirmed. Although there was a difference in the results for the "giin-flag", the difference was small, and no advantage was found with or without the "giin-flag".
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Nishihara et al. (2022) studied this question.
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