About

Entity Disambiguation is the task of linking mentions of ambiguous entities to their referent entities in a knowledge base such as Wikipedia.

Source: Leveraging Deep Neural Networks and Knowledge Graphs for Entity Disambiguation

Benchmarks

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Datasets

Latest papers with code

Autoregressive Entity Retrieval

ICLR 2021 facebookresearch/GENRE

For instance, Encyclopedias such as Wikipedia are structured by entities (e. g., one per article).

ENTITY DISAMBIGUATION ENTITY LINKING OPEN-DOMAIN QUESTION ANSWERING

135
02 Oct 2020

Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models

12 Aug 2020mulangonando/Impact-of-KG-Context-on-ED

We further hypothesize that our proposed KG context can be standardized for Wikipedia, and we evaluate the impact of KG context on state-of-the-art NED model for the Wikipedia knowledge base.

ENTITY DISAMBIGUATION

8
12 Aug 2020

Improving Broad-Coverage Medical Entity Linking with Semantic Type Prediction and Large-Scale Datasets

1 May 2020svjan5/medtype

To address the dearth of annotated training data for medical entity linking, we present WikiMed and PubMedDS, two large-scale medical entity linking datasets, and demonstrate that pre-training MedType on these datasets further improves entity linking performance.

ENTITY DISAMBIGUATION ENTITY LINKING TRANSFER LEARNING TYPE PREDICTION

48
01 May 2020

Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking

CONLL 2019 samuelbroscheit/entity_knowledge_in_bert

We show on an entity linking benchmark that (i) this model improves the entity representations over plain BERT, (ii) that it outperforms entity linking architectures that optimize the tasks separately and (iii) that it only comes second to the current state-of-the-art that does mention detection and entity disambiguation jointly.

Ranked #3 on Entity Linking on AIDA-CoNLL (using extra training data)

ENTITY DISAMBIGUATION ENTITY LINKING MACHINE TRANSLATION QUESTION ANSWERING

23
11 Mar 2020

EntEval: A Holistic Evaluation Benchmark for Entity Representations

IJCNLP 2019 ZeweiChu/EntEval

Rich entity representations are useful for a wide class of problems involving entities.

ENTITY DISAMBIGUATION ENTITY TYPING

19
31 Aug 2019

Uncovering the Semantics of Wikipedia Categories

28 Jun 2019nheist/Cat2Ax

The Wikipedia category graph serves as the taxonomic backbone for large-scale knowledge graphs like YAGO or Probase, and has been used extensively for tasks like entity disambiguation or semantic similarity estimation.

ENTITY DISAMBIGUATION KNOWLEDGE GRAPHS SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY

4
28 Jun 2019

Neural Collective Entity Linking Based on Recurrent Random Walk Network Learning

20 Jun 2019DeepLearnXMU/RRWEL

However, most neural collective EL methods depend entirely upon neural networks to automatically model the semantic dependencies between different EL decisions, which lack of the guidance from external knowledge.

ENTITY DISAMBIGUATION ENTITY LINKING LEARNING SEMANTIC REPRESENTATIONS

28
20 Jun 2019

Be Concise and Precise: Synthesizing Open-Domain Entity Descriptions from Facts

16 Apr 2019kingsaint/Wikidata-Descriptions

Despite being vast repositories of factual information, cross-domain knowledge graphs, such as Wikidata and the Google Knowledge Graph, only sparsely provide short synoptic descriptions for entities.

ENTITY DISAMBIGUATION KNOWLEDGE GRAPHS

3
16 Apr 2019

Entity Synonym Discovery via Multipiece Bilateral Context Matching

31 Dec 2018czhang99/SynonymNet

Being able to automatically discover synonymous entities in an open-world setting benefits various tasks such as entity disambiguation or knowledge graph canonicalization.

ENTITY DISAMBIGUATION

15
31 Dec 2018