Entity Disambiguation

38 papers with code • 8 benchmarks • 8 datasets

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

Greatest papers with code

Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation

wikipedia2vec/wikipedia2vec CONLL 2016

The KB graph model learns the relatedness of entities using the link structure of the KB, whereas the anchor context model aims to align vectors such that similar words and entities occur close to one another in the vector space by leveraging KB anchors and their context words.

Entity Disambiguation Entity Linking

DeepType: Multilingual Entity Linking by Neural Type System Evolution

openai/deeptype 3 Feb 2018

The wealth of structured (e. g. Wikidata) and unstructured data about the world available today presents an incredible opportunity for tomorrow's Artificial Intelligence.

Entity Disambiguation Entity Embeddings +2

Multilingual Autoregressive Entity Linking

facebookresearch/GENRE 23 Mar 2021

Moreover, in a zero-shot setting on languages with no training data at all, mGENRE treats the target language as a latent variable that is marginalized at prediction time.

Ranked #2 on Entity Disambiguation on Mewsli-9 (using extra training data)

Entity Disambiguation Entity Linking

Autoregressive Entity Retrieval

facebookresearch/GENRE ICLR 2021

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

Entity Disambiguation Entity Linking +2

Global Entity Disambiguation with Pretrained Contextualized Embeddings of Words and Entities

studio-ousia/luke 1 Sep 2019

We propose a new global entity disambiguation (ED) model based on contextualized embeddings of words and entities.

Entity Disambiguation Language Modelling

End-to-End Neural Entity Linking

dalab/end2end_neural_el CONLL 2018

Entity Linking (EL) is an essential task for semantic text understanding and information extraction.

Entity Disambiguation Entity Embeddings +2

Deep Joint Entity Disambiguation with Local Neural Attention

dalab/deep-ed EMNLP 2017

We propose a novel deep learning model for joint document-level entity disambiguation, which leverages learned neural representations.

Document-level Entity Disambiguation

Entity Disambiguation with Web Links

wikilinks/nel TACL 2015

Entity disambiguation with Wikipedia relies on structured information from redirect pages, article text, inter-article links, and categories.

Entity Disambiguation Entity Linking +1

Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation

HazyResearch/bootleg 20 Oct 2020

A challenge for named entity disambiguation (NED), the task of mapping textual mentions to entities in a knowledge base, is how to disambiguate entities that appear rarely in the training data, termed tail entities.

Entity Disambiguation Relation Extraction

Studying the Wikipedia Hyperlink Graph for Relatedness and Disambiguation

asoroa/ukb 5 Mar 2015

Hyperlinks and other relations in Wikipedia are a extraordinary resource which is still not fully understood.

Entity Disambiguation