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

arXiv: https://arxiv.org/abs/2204.06347 · HTML: https://mlsanity.com/paper/2204.06347/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 38 references that are in the map.
- First posted on arXiv 13 Apr 2022.

## Builds on (most cited first, 17 of 17)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Dense Passage Retrieval for Open-Domain Question Answering](https://mlsanity.com/paper/2004.04906/) (2020)
- [SimCSE: Simple Contrastive Learning of Sentence Embeddings](https://mlsanity.com/paper/2104.08821/) (2021)
- [LXMERT: Learning Cross-Modality Encoder Representations from Transformers](https://mlsanity.com/paper/1908.07490/) (2019)
- [Autoregressive Entity Retrieval](https://mlsanity.com/paper/2010.00904/) (2020)
- [Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers](https://mlsanity.com/paper/2004.00849/) (2020)
- [Few-NERD: A Few-Shot Named Entity Recognition Dataset](https://mlsanity.com/paper/2105.07464/) (2021)
- [Zero-Shot Entity Linking by Reading Entity Descriptions](https://mlsanity.com/paper/1906.07348/) (2019)
- [Visual News: Benchmark and Challenges in News Image Captioning](https://mlsanity.com/paper/2010.03743/) (2020)
- [Deep Joint Entity Disambiguation with Local Neural Attention](https://mlsanity.com/paper/1704.04920/) (2017)
- [Good News, Everyone! Context driven entity-aware captioning for news images](https://mlsanity.com/paper/1904.01475/) (2019)
- [Improving Entity Linking by Modeling Latent Relations between Mentions](https://mlsanity.com/paper/1804.10637/) (2018)
- [Transform and Tell: Entity-Aware News Image Captioning](https://mlsanity.com/paper/2004.08070/) (2020)
- [Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation](https://mlsanity.com/paper/1601.01343/) (2016)
- [Multimodal Entity Linking for Tweets](https://mlsanity.com/paper/2104.03236/) (2021)

## Built on by (most cited first, 30 of 34)

- [Large Language Models for Generative Information Extraction: A Survey](https://mlsanity.com/paper/2312.17617/) (2023)
- [A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodal](https://mlsanity.com/paper/2212.05767/) (2022)
- [GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation](https://mlsanity.com/paper/2303.14655/) (2023)
- [Named Entity and Relation Extraction with Multi-Modal Retrieval](https://mlsanity.com/paper/2212.01612/) (2022)
- [SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding](https://mlsanity.com/paper/2308.10529/) (2023)
- [Retrieval-based Knowledge Augmented Vision Language Pre-training](https://mlsanity.com/paper/2304.13923/) (2023)
- [Visual Named Entity Linking: A New Dataset and A Baseline](https://mlsanity.com/paper/2211.04872/) (2022)
- [Multi-Grained Multimodal Interaction Network for Entity Linking](https://mlsanity.com/paper/2307.09721/) (2023)
- [MESED: A Multi-modal Entity Set Expansion Dataset with Fine-grained Semantic Classes and Hard Negative Entities](https://mlsanity.com/paper/2307.14878/) (2023)
- [Generative Multimodal Entity Linking](https://mlsanity.com/paper/2306.12725/) (2023)
- [A Dual-way Enhanced Framework from Text Matching Point of View for Multimodal Entity Linking](https://mlsanity.com/paper/2312.11816/) (2023)
- [Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities](https://mlsanity.com/paper/2309.17255/) (2023)
- [Knowledge-Aware Reasoning over Multimodal Semi-structured Tables](https://mlsanity.com/paper/2408.13860/) (2024)
- [AMELI: Enhancing Multimodal Entity Linking with Fine-Grained Attributes](https://mlsanity.com/paper/2305.14725/) (2023)
- [DRIN: Dynamic Relation Interactive Network for Multimodal Entity Linking](https://mlsanity.com/paper/2310.05589/) (2023)
- [Benchmarking Diverse-Modal Entity Linking with Generative Models](https://mlsanity.com/paper/2305.17337/) (2023)
- [Optimal Transport Guided Correlation Assignment for Multimodal Entity Linking](https://mlsanity.com/paper/2406.01934/) (2024)
- [UniMEL: A Unified Framework for Multimodal Entity Linking with Large Language Models](https://mlsanity.com/paper/2407.16160/) (2024)
- [KGMEL: Knowledge Graph-Enhanced Multimodal Entity Linking](https://mlsanity.com/paper/2504.15135/) (2025)
- [Enhancing Multimodal Entity Linking with Jaccard Distance-based Conditional Contrastive Learning and Contextual Visual Augmentation](https://mlsanity.com/paper/2501.14166/) (2025)
- [DeepMEL: A Multi-Agent Collaboration Framework for Multimodal Entity Linking](https://mlsanity.com/paper/2508.15876/) (2025)
- [Multi-level Matching Network for Multimodal Entity Linking](https://mlsanity.com/paper/2412.10440/) (2024)
- [OVEL: Large Language Model as Memory Manager for Online Video Entity Linking](https://mlsanity.com/paper/2403.01411/) (2024)
- [DIM: Dynamic Integration of Multimodal Entity Linking with Large Language Model](https://mlsanity.com/paper/2407.12019/) (2024)
- [A Benchmark Dataset and a Framework for Urdu Multimodal Named Entity Recognition](https://mlsanity.com/paper/2505.05148/) (2025)
- [MERLIN: A Testbed for Multilingual Multimodal Entity Recognition and Linking](https://mlsanity.com/paper/2510.14307/) (2025)
- [Multi-Perspective Evidence Synthesis and Reasoning for Unsupervised Multimodal Entity Linking](https://mlsanity.com/paper/2604.20283/) (2026)
- [Revealing Trends in Datasets from the 2022 ACL and EMNLP Conferences](https://mlsanity.com/paper/2404.08666/) (2024)
- [M3EL: A Multi-task Multi-topic Dataset for Multi-modal Entity Linking](https://mlsanity.com/paper/2410.18096/) (2024)
- [VP-MEL: Visual Prompts Guided Multimodal Entity Linking](https://mlsanity.com/paper/2412.06720/) (2024)

## Abstract (arXiv)

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