The OUC team participated in the Budget Argument Mining subtask of NTCIR-16 Question Answering Lab for Political Information 3 (QA Lab-PoliInfo-3). In this paper, we report on our methods for this task and discuss the results. We performed argument classification using a fine-tuned BERT classifier. This method showed the second highest score (0.5716) among the participants in the test data. We also performed linking relatedID using TF-IDF vectorization of documents and calculation of their cosine similarity. This method showed the highest score (0.6596) among the participants in the test data.
Nagafuchi et al. (2022) studied this question.