OUC team demonstrates effective argument classification using BERT, highlighting significant findings in political information processing.
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.
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Nagafuchi et al. (2022) studied this question.
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