Table question answering is a popular task that assesses a model's ability to
understand and interact with structured data. However, the given table often
does not contain sufficient information for answering the question,
necessitating the integration of external knowledge. Existing methods either
convert both the table and external knowledge into text, which neglects the
structured nature of the table; or they embed queries for external sources in
the interaction with the table, which complicates the process. In this paper,
we propose a simple yet effective method to integrate external information in a
given table. Our method first constructs an augmenting table containing the
missing information and then generates a SQL query over the two tables to
answer the question. Experiments show that our method outperforms strong
baselines on three table QA benchmarks. Our code is publicly available at
this https URL

本研究提出了一种简单而有效的方法，用于在给定的表格中集成外部信息，通过构建一个包含缺失信息的增强表格，然后生成两个表格的 SQL 查询来回答问题。实验证明，我们的方法在三个表格问答基准测试上优于强基准模型。