| Budget Amount *help |
¥44,980,000 (Direct Cost: ¥34,600,000、Indirect Cost: ¥10,380,000)
Fiscal Year 2023: ¥6,240,000 (Direct Cost: ¥4,800,000、Indirect Cost: ¥1,440,000)
Fiscal Year 2022: ¥8,580,000 (Direct Cost: ¥6,600,000、Indirect Cost: ¥1,980,000)
Fiscal Year 2021: ¥10,400,000 (Direct Cost: ¥8,000,000、Indirect Cost: ¥2,400,000)
Fiscal Year 2020: ¥11,310,000 (Direct Cost: ¥8,700,000、Indirect Cost: ¥2,610,000)
Fiscal Year 2019: ¥8,450,000 (Direct Cost: ¥6,500,000、Indirect Cost: ¥1,950,000)
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| Outline of Final Research Achievements |
The research was carried out with an awareness of the trend in natural language processing research of the large language models. The research project advances language understanding, inference, and argumentation mining through studies on acquiring lexical knowledge from static word embeddings, adapting dynamic word embeddings to an existing ontology, language understanding from SNS text, aspect-based sentiment analysis based on generative language models, estimating confidence of natural language inference, predicting whether a language model is trained on a pre-training corpus with a targe knowledge, stance detection for each agenda item from meeting minutes, explaining the results of aspect-based sentiment analysis.
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