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Multimodal Entity Linking (MEL) which aims at linking mentions withmultimodal contexts to the referent entities from a knowledge base (e.g.,Wikipedia), is an essential task for many multimodal applications. Althoughmuch attention has been paid to MEL, the shortcomings of existing MEL datasetsincluding limited contextual topics and entity types, simplified mentionambiguity, and restricted availability, have caused great obstacles to theresearch and application of MEL. In this paper, we present WikiDiverse, ahigh-quality human-annotated MEL dataset with diversified contextual topics andentity types from Wikinews, which uses Wikipedia as the corresponding knowledgebase. A well-tailored annotation procedure is adopted to ensure the quality ofthe dataset. Based on WikiDiverse, a sequence of well-designed MEL models withintra-modality and inter-modality attentions are implemented, which utilize thevisual information of images more adequately than existing MEL models do.Extensive experimental analyses are conducted to investigate the contributionsof different modalities in terms of MEL, facilitating the future research onthis task. The dataset and baseline models are available athttps://github.com/wangxw5/wikiDiverse.

WikiDiverse: A Multimodal Entity Linking Dataset with Diversified Contextual Topics and Entity Types