人工知能学会全国大会論文集
Online ISSN : 2758-7347
37th (2023)
セッションID: 1U5-IS-2b-03
会議情報

Enhancing Financial Question Answering with Structured Knowledge
*Rungsiman NARARATWONGNatthawut KERTKEIDKACHORNZiwei XURyutaro ICHISE
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Answering questions involving financial documents using a language model requires the ability to recognize tabular and textual data, as well as numerical reasoning. This article explains the challenges, recent progress, and our approach to tackling this problem by incorporating external structured knowledge. We also introduce our financial knowledge graph (KG) linking companies to people, industries, and facts extracted from public financial filings. The KG is part of our work to advance machine-learning models for more complex financial questions beyond the scope of the previous models and datasets.

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© 2023 The Japanese Society for Artificial Intelligence
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