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BERTScore is an effective and robust automatic metric for referencebasedmachine translation evaluation. In this paper, we incorporate multilingualknowledge graph into BERTScore and propose a metric named KG-BERTScore, whichlinearly combines the results of BERTScore and bilingual named entity matchingfor reference-free machine translation evaluation. From the experimentalresults on WMT19 QE as a metric without references shared tasks, our metricKG-BERTScore gets higher overall correlation with human judgements than thecurrent state-of-the-art metrics for reference-free machine translationevaluation.1 Moreover, the pre-trained multilingual model used by KG-BERTScoreand the parameter for linear combination are also studied in this paper.

KG-BERTScore: Incorporating Knowledge Graph into BERTScore for Reference-Free Machine Translation Evaluation