Jingyi Li


2020

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Fact-based Content Weighting for Evaluating Abstractive Summarisation
Xinnuo Xu | Ondřej Dušek | Jingyi Li | Verena Rieser | Ioannis Konstas
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Abstractive summarisation is notoriously hard to evaluate since standard word-overlap-based metrics are insufficient. We introduce a new evaluation metric which is based on fact-level content weighting, i.e. relating the facts of the document to the facts of the summary. We fol- low the assumption that a good summary will reflect all relevant facts, i.e. the ones present in the ground truth (human-generated refer- ence summary). We confirm this hypothe- sis by showing that our weightings are highly correlated to human perception and compare favourably to the recent manual highlight- based metric of Hardy et al. (2019).