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Entity linking

In natural language processing, entity linking, also referred to as named-entity disambiguation (NED), named-entity recognition and disambiguation (NERD), named-entity normalization (NEN), or concept recognition, is the task of assigning a unique identity to entities (such as famous individuals, locations, or companies) mentioned in text. For example…

Applications & Companies

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Research this topic

Explore the main themes, entities and connections around Entity linking. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

Introduction

Applications

Related concepts

Approaches

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Entity linking

Nodes53
Edges52
Triples110
Avg. degree1.96
Density0.037736
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Entity linking

Top relations

related to Challenges · 30
Entity linking → Absence, Ambiguity, Big Apple, Ensuring, Evolving, Examples, For, France's, French, However, Ideally, In, Knowing, Multiple, Name, New, New York, NY, Others, Paris
related to Mathematical · 20
Entity linking → AnnoMathTeX, DLMF, Formulae, Furthermore, Interest, It, MathEL, Mathematical, Mathematical Entity Linking, Mathematical Functions, Mathematical Objects, MathMLben, MOI, NIST Digital Library, The, This, To, Wikidata, Wikimedia, Wikipedia
related to Introduction · 16
Entity linking → Considering, DBpedia, Entity, France, In, NEs, Paris, The, These, URI, URIs, URLs, Using, Wikidata, Wikipedia, Words
related to Text-based · 10
Entity linking → Cucerzan, Cucerzan's, First, Rao, Specifically, SVM, The, Then, This, Wikipedia
has application · 9
Entity linking → Consider, Entity, Even, FN, For, FP, France, In, Paris
related to Graph-based · 7
Entity linking → Graph-based, Han, Modern, Moreover, NLP, This, Wikipedia
related to Related concepts · 5
Entity linking → Alhelbawy, Definitions, Entity, Named-entity, NED
related to Approaches · 3
Entity linking → Broadly, Entity, Many
is a · 1
Entity linking → critical step to bridge web data with knowledge bases

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

entity linking entities knowledge wikipedia text base example paris disambiguation named france systems system also capital mathematical search textual features

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Entity linkingis acritical step to bridge web data with knowledge bases0.90text
namesinstance oflocates and classifies named entities in unstructured text into pre-defined categories0.80text
organizationsinstance oflocates and classifies named entities in unstructured text into pre-defined categories0.80text
locationsinstance oflocates and classifies named entities in unstructured text into pre-defined categories0.80text
and moreinstance oflocates and classifies named entities in unstructured text into pre-defined categories0.80text
Wikipediainstance ofOther approaches also collected training data based on unambiguous synonyms.Graph-basedModern entity linking systems also use large knowledge graphs created from knowledge bases0.80text
besides textual features generated from input documents or text corporainstance ofOther approaches also collected training data based on unambiguous synonyms.Graph-basedModern entity linking systems also use large knowledge graphs created from knowledge bases0.80text
PageRankinstance ofalgorithms0.80text
Wikipediainstance ofGraph-basedModern entity linking systems also use large knowledge graphs created from knowledge bases0.80text
besides textual features generated from input documents or text corporainstance ofGraph-basedModern entity linking systems also use large knowledge graphs created from knowledge bases0.80text
Entity linkinghas applicationEntity0.60section
Entity linkinghas applicationIn0.60section

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
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