ACL2021

BioGen: Generating Biography Summary under Table Guidance on Wikipedia

Shen Gao, Xiuying Chen, Chang Liu, Dongyan Zhao, Rui Yan

Abstract

Capturing the salient information from an input article has been a long-standing challenge for summarization. On Wikipedia, most of the wiki pages about people contain a factual table that lists the basic properties of the people. Illuminatingly, a factual table can be regarded as a natural summary of the key information in the corresponding article. Thus, in this paper we propose the task of tableguided abstractive biography summarization, which utilizes factual tables to capture important information and then generate a summary of a biography. We first introduce the TaGS (Table-Guided Summarization) dataset 1 , the first large-scale biography summarization dataset with tables. Next, we report some statistics about this dataset to validate the quality of the dataset. We also benchmark several commonly used summarization methods on TaGS and hope this will inspire more exciting methods.