mlsanityData to 14 Oct 2026

Entity Linking Meets Deep Learning: Techniques and Solutions

arXiv 2109.12520 ↗First posted 26 Sep 2021cs.CL cs.AIcited by 22

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Abstract (arXiv)

Entity linking (EL) is the process of linking entity mentions appearing in web text with their corresponding entities in a knowledge base. EL plays an important role in the fields of knowledge engineering and data mining, underlying a variety of downstream applications such as knowledge base population, content analysis, relation extraction, and question answering. In recent years, deep learning (DL), which has achieved tremendous success in various domains, has also been leveraged in EL methods to surpass traditional machine learning based methods and yield the state-of-the-art performance. In this survey, we present a comprehensive review and analysis of existing DL based EL methods. First of all, we propose a new taxonomy, which organizes existing DL based EL methods using three axes: embedding, feature, and algorithm. Then we systematically survey the representative EL methods along the three axes of the taxonomy. Later, we introduce ten commonly used EL data sets and give a quantitative performance analysis of DL based EL methods over these data sets. Finally, we discuss the remaining limitations of existing methods and highlight some promising future directions.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 54 of its 148 references that are in the map. First posted on arXiv 26 Sep 2021.

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54 of 148 references.

References · 54

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38 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 4; 2023: 4; 2024: 5; 2025: 8; 2026: 1.

22 papers.

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  1. 2024ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphscited by 85
  2. 2022TIARA: Multi-grained Retrieval for Robust Question Answering over Large Knowledge Basescited by 59
  3. 2024KG-RAG: Bridging the Gap Between Knowledge and Creativitycited by 56
  4. 2025MMGraphRAG: Bridging Vision and Language with Interpretable Multimodal Knowledge Graphscited by 16
  5. 2024Learning to Extract Structured Entities Using Language Modelscited by 8
  6. 2025Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questionscited by 8
  7. 2023Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity Linkingcited by 7
  8. 2023Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity Linkingcited by 7
  9. 2022Community Question Answering Entity Linking via Leveraging Auxiliary Datacited by 5
  10. 2022Multi-View Clustering for Open Knowledge Base Canonicalizationcited by 5
  11. 2022Learning Entity Linking Features for Emerging Entitiescited by 2
  12. 2024Span-Oriented Information Extraction -- A Unifying Perspective on Information Extractioncited by 2
10 more
  1. 2025Trusted Knowledge Extraction for Operations and Maintenance Intelligencecited by 2
  2. 2023NLP Workbench: Efficient and Extensible Integration of State-of-the-art Text Mining Toolscited by 1
  3. 2025CDE-Mapper: Using Retrieval-Augmented Language Models for Linking Clinical Data Elements to Controlled Vocabulariescited by 1
  4. 2023Matching of Descriptive Labels to Glossary Descriptionscited by 0
  5. 2024Enriching Social Science Research via Survey Item Linkingcited by 0
  6. 2025Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Modelscited by 0
  7. 2025Entity-Augmented Neuroscience Knowledge Retrieval Using Ontology and Semantic Understanding Capability of LLMcited by 0
  8. 2025I2CR: Intra- and Inter-modal Collaborative Reflections for Multimodal Entity Linkingcited by 0
  9. 2025PGMEL: Policy Gradient-based Generative Adversarial Network for Multimodal Entity Linkingcited by 0
  10. 2026KARAMEL: Knowledge-Aware Ranking for Multimodal Entity Linking in the Arts via Heterogeneous Graphscited by 0