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

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Datasets

Greatest papers with code

Probabilistic Bag-Of-Hyperlinks Model for Entity Linking

8 Sep 2015dalab/pboh-entity-linking

We here propose a probabilistic approach that makes use of an effective graphical model to perform collective entity disambiguation.

ENTITY DISAMBIGUATION ENTITY LINKING FEATURE ENGINEERING MACHINE TRANSLATION

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

Named Entity Disambiguation using Deep Learning on Graphs

22 Oct 2018ContextScout/ned-graphs

We tackle \ac{NED} by comparing entities in short sentences with \wikidata{} graphs.

ENTITY DISAMBIGUATION

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

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

ELDEN: Improved Entity Linking Using Densified Knowledge Graphs

NAACL 2018 priyaradhakrishnan0/ELDEN

Entity Linking (EL) systems aim to automatically map mentions of an entity in text to the corresponding entity in a Knowledge Graph (KG).

ENTITY DISAMBIGUATION ENTITY EMBEDDINGS ENTITY LINKING KNOWLEDGE GRAPHS

Collective Entity Disambiguation with Structured Gradient Tree Boosting

NAACL 2018 bloomberg/sgtb

To the best of our knowledge, our work is the first one that employs the structured gradient tree boosting (SGTB) algorithm for collective entity disambiguation.

ENTITY DISAMBIGUATION

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

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