Entity linking for English and other languages: a survey

Imane Guellil*, Antonio Garcia-Dominguez, Peter R. Lewis, Shakeel Hussain, Geoffrey Smith

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Extracting named entities text forms the basis for many crucial tasks such as information retrieval and extraction, machine translation, opinion mining, sentiment analysis and question answering. This paper presents a survey of the research literature on named entity linking, including named entity recognition and disambiguation. We present 200 works by focusing on 43 papers (5 surveys and 38 research works). We also describe and classify 56 resources, including 25 tools and 31 corpora. We focus on the most recent papers, where more than 95% of the described research works are after 2015. To show the efficiency of our construction methodology and the importance of this state of the art, we compare it to other surveys presented in the research literature, which were based on different criteria (such as the domain, novelty and presented models and resources). We also present a set of open issues (including the dominance of the English language in the proposed studies and the frequent use of NER rather than the end-to-end systems proposing NED and EL) related to entity linking based on the research questions that this survey aims to answer.

Original languageEnglish
Number of pages52
JournalKnowledge and Information Systems
Publication statusPublished - 2 Apr 2024

Bibliographical note

Funding Information:
The research reported in this paper was funded by the Innovate UK-funded Knowledge Transfer Partnership (ref. KTP011673) between Aston University and Folding Space.

Publisher Copyright:
© The Author(s) 2024.


  • English entity linking approaches
  • Entity linking
  • Multilingual entity linking approaches
  • Named entity disambiguation
  • Named entity recognition

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