Entity Disambiguation Edit Task
Natural Language Processing
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).
Ranked #1 on
Entity Linking
on KILT: WNED-WIKI
ENTITY DISAMBIGUATION ENTITY LINKING OPEN-DOMAIN QUESTION ANSWERING
PNEL: Pointer Network based End-To-End Entity Linking over Knowledge Graphs
In such a pipeline, Entity Linking (EL) is often the first step.
ENTITY DISAMBIGUATION ENTITY LINKING KNOWLEDGE GRAPHS QUESTION ANSWERING
Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models
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.
Ranked #2 on
Entity Disambiguation
on AIDA-CoNLL
Improving Broad-Coverage Medical Entity Linking with Semantic Type Prediction and Large-Scale Datasets
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
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
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.
Uncovering the Semantics of Wikipedia Categories
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
Neural Collective Entity Linking Based on Recurrent Random Walk Network Learning
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
Be Concise and Precise: Synthesizing Open-Domain Entity Descriptions from Facts
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 Synonym Discovery via Multipiece Bilateral Context Matching
Being able to automatically discover synonymous entities in an open-world setting benefits various tasks such as entity disambiguation or knowledge graph canonicalization.