MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data

Yilun Zhao, Yunxiang Li, Chenying Li, Rui Zhang


Abstract
Numerical reasoning over hybrid data containing both textual and tabular content (e.g., financial reports) has recently attracted much attention in the NLP community. However, existing question answering (QA) benchmarks over hybrid data only include a single flat table in each document and thus lack examples of multi-step numerical reasoning across multiple hierarchical tables. To facilitate data analytical progress, we construct a new large-scale benchmark, MultiHiertt, with QA pairs over Multi Hierarchical Tabular and Textual data. MultiHiertt is built from a wealth of financial reports and has the following unique characteristics: 1) each document contain multiple tables and longer unstructured texts; 2) most of tables contained are hierarchical; 3) the reasoning process required for each question is more complex and challenging than existing benchmarks; and 4) fine-grained annotations of reasoning processes and supporting facts are provided to reveal complex numerical reasoning. We further introduce a novel QA model termed MT2Net, which first applies facts retrieving to extract relevant supporting facts from both tables and text and then uses a reasoning module to perform symbolic reasoning over retrieved facts. We conduct comprehensive experiments on various baselines. The experimental results show that MultiHiertt presents a strong challenge for existing baselines whose results lag far behind the performance of human experts. The dataset and code are publicly available at https://github.com/psunlpgroup/MultiHiertt.
Anthology ID:
2022.acl-long.454
Volume:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6588–6600
Language:
URL:
https://aclanthology.org/2022.acl-long.454
DOI:
10.18653/v1/2022.acl-long.454
Bibkey:
Cite (ACL):
Yilun Zhao, Yunxiang Li, Chenying Li, and Rui Zhang. 2022. MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 6588–6600, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data (Zhao et al., ACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.acl-long.454.pdf
Code
 psunlpgroup/multihiertt
Data
DROPFinQAHybridQAMATHMathQATAT-QA