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KGQA-leaderboard

Repository to track the progress in Question Answering over Knowledge Graphs (KGQA), including the datasets and the current state-of-the-art for the most common KGQA tasks.

Covid-19QA

Covid-19QA [1]</sup> is a new Covid-19 related QA dataset, where the questions were generated from six kinds of “wh” question templates. All of questions require one-hop reasoning. This dataset is based on COVID-19KG, a knowledge graph about Covid-19 via Named Entity Recognition and Relation Extraction algorithms from PubMed biomedical texts. Covid-19KG contains 11,264 entities, 8,038 relations, and 123,190 triples.

Leaderboard

Model / System Year Hits@1 Language Reported by
Qiao et al.’s proposed method 2022 29.00 EN Qiao et al.
EmbedKGQA 2022 27.7 EN Qiao et al.
EmbedWBioBERT 2022 7.50 EN Qiao et al.
EmbedWBERT 2022 6.40 EN Qiao et al.

References

[1] Qiao, Yinbo and Yang, Zhihao and Lin, Hongfei and Wang, Jian. An End-to-End Knowledge Graph Based Question Answering Approach for COVID-19. In China Health Information Processing Conference, pp. 156–169. 2022.

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