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arXiv · 2508.00476

GETALP@AutoMin 2025: Leveraging RAG to Answer Questions based on Meeting Transcripts

Jeongwoo Kang·Markarit Vartampetian·Felix Herron·Yongxin Zhou·Diandra Fabre·Gabriela Gonzalez-Saez
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Abstract

This paper documents GETALP's submission to the Third Run of the Automatic Minuting Shared Task at SIGDial 2025. We participated in Task B: question-answering based on meeting transcripts. Our method is based on a retrieval augmented generation (RAG) system and Abstract Meaning Representations (AMR). We propose three systems combining these two approaches. Our results show that incorporating AMR leads to high-quality responses for approximately 35% of the questions and provides notable improvements in answering questions that involve distinguishing between different participants (e.g., who questions).

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Jeongwoo Kang, Markarit Vartampetian, Felix Herron, Yongxin Zhou, Diandra Fabre, Gabriela Gonzalez-Saez. 2025-08-01. GETALP@AutoMin 2025: Leveraging RAG to Answer Questions based on Meeting Transcripts. https://arxiv.org/abs/2508.00476

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