Abstract
Large language models (LLMs) show powerful reasoning abilities on various text-based tasks. However, their reasoning capability on structured data such as tables has not been systematically explored. In this work, we first establish a comprehensive taxonomy of reasoning and operation types for tabular data analysis. Then, we construct a complex reasoning QA dataset over tabular data, named CRT-QA dataset (Complex Reasoning QA over Tabular data), with the following unique features: (1) it is the first Table QA dataset with multi-step operation and informal reasoning; (2) it contains fine-grained annotations on questions’ directness, composition types of sub-questions, and human reasoning paths which can be used to conduct a thorough investigation on LLMs’ reasoning ability; (3) it contains a collection of unanswerable and indeterminate questions that commonly arise in real-world situations. We further introduce an efficient and effective tool-augmented method, named ARC (Auto-exemplar-guided Reasoning with Code), to use external tools such as Pandas to solve table reasoning tasks without handcrafted demonstrations. The experiment results show that CRT-QA presents a strong challenge for baseline methods and ARC achieves the best result.- Anthology ID:
- 2023.emnlp-main.132
- Volume:
- Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2131–2153
- Language:
- URL:
- https://aclanthology.org/2023.emnlp-main.132
- DOI:
- 10.18653/v1/2023.emnlp-main.132
- Cite (ACL):
- Zhehao Zhang, Xitao Li, Yan Gao, and Jian-Guang Lou. 2023. CRT-QA: A Dataset of Complex Reasoning Question Answering over Tabular Data. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 2131–2153, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- CRT-QA: A Dataset of Complex Reasoning Question Answering over Tabular Data (Zhang et al., EMNLP 2023)
- PDF:
- https://preview.aclanthology.org/corrections-2024-05/2023.emnlp-main.132.pdf