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Multimodal entity linking (MEL) aims to utilize multimodal information to map mentions to corresponding entities defined in knowledge bases. We release three MEL datasets: Weibo-MEL, Wikidata-MEL and Richpedia-MEL, containing 25,602, 18,880 and 17,806 samples from social media, encyclopedia and multimodal knowledge graphs respectively. A MEL dataset construction approach is proposed, including five stages: multimodal information extraction, mention extraction, entity extraction, triple construction and dataset construction. Experiment results demonstrate the usability of the datasets and the distinguishability between baseline models.

License: MIT License

entity-linking knowledge-graph multimodal

melbench's Issues

数据集图片

你好,我关注到您的相关数据集图片部分发布在百度网盘中,但并无提取码,请问怎么获取?

RichpediaMEL里每条数据的图片怎么找?

您好,我是汪老师的学生。RichpediaMEL里每条数据并未给出实体对应的图片名或者路径,从网盘下载图片也未能从图片名中看出端倪,请问实体与图片之间是怎么对应的?

train/valid/test split

Hello,

Thank you for releasing this well-formatted multimodal entity linking dataset! I'm wondering when will the training/valid/test splits be shared?

数据集实体标注疑问

您好!感谢您提供的数据集。
我发现在句子中提及的entity并没有被全部标注出来。例如readme中例子中的“北海舰队”和“Seattle”,都是entity。但是没有标注。请问这是什么原因呢?
谢谢~

Where is the password of Baidu Cloud Disk

I don't find the password of Baidu Cloud Disk, could you add it in the README.md ?
another issue is that whether the database of Weibo-MEL is Wikidata Knowledge Graph

baseline 分数

Hi,校友们~

我最近在尝试用你们提供的mel数据做实验,非常好的工作!
想请问,这几个数据集你们有baseline的方案和F1可以report吗?我想知道自己做到什么程度了。

Thanks

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