[1U5-IS-2b] Machine learning

[1U5-IS-2b-03] Enhancing Financial Question Answering with Structured Knowledge

〇Rungsiman Nararatwong¹, Natthawut Kertkeidkachorn², Ziwei Xu¹, Ryutaro Ichise^3,1 (1. National Institute of Advanced Industrial Science and Technology, 2. Japan Advanced Institute of Science and Technology, 3. Tokyo Institute of Technology)

[[Online, Regular]]

Keywords:Question Answering, Knowledge Graph, Finance

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.