We present the results of the Workshop on Multilingual Information Access
(MIA) 2022 Shared Task, evaluating cross-lingual open-retrieval question
answering (QA) systems in 16 typologically diverse languages. In this task, we
adapted two large-scale cross-lingual open-retrieval QA datasets in 14
typologically diverse languages, and newly annotated open-retrieval QA data in
2 underrepresented languages: Tagalog and Tamil. Four teams submitted their
systems. The best system leveraging iteratively mined diverse negative examples
and larger pretrained models achieves 32.2 F1, outperforming our baseline by
4.5 points. The second best system uses entity-aware contextualized
representations for document retrieval, and achieves significant improvements
in Tamil (20.8 F1), whereas most of the other systems yield nearly zero scores.

本文介绍了 MIA 2022 workshop 关于跨语言信息检索中的开放式提取问题回答（QA）系统评估的结果，并评估了 16 种语言中的系统性能表现。通过对 14 种语言的大规模跨语言开放式提取 QA 数据集进行改编以及对 Tagalog 和 Tamil 两种语言进行新的标记，共有 4 支队伍提交了他们的系统，最佳系统借助多样化的负样本和更大的预训练模型实现了 32.2 的 F1 值，而第二名则在 Tamil 语言的检索中取得了显著的进展。