Results 11 to 20 of about 20,627 (210)

SNEToolkit: Spatial named entities disambiguation toolkit [PDF]

SoftwareX, 2023
“Can you tell me where San Jose is located?” “Uh! Do you know that there are more than 1700 locations named San Jose in the world?” The official name of a location is often not the name with which we are familiar.
Rodrique Kafando, Rémy Decoupes, Mathieu Roche, Maguelonne Teisseire   +3 more
doaj   +4 more sources

BELHD: improving biomedical entity linking with homonym disambiguation. [PDF]

Bioinformatics
Abstract Motivation Biomedical entity linking (BEL) is the task of grounding entity mentions to a given knowledge base (KB). Recently, neural name-based methods, system identifying the most appropriate name in the KB for a given mention using neural network (either via dense retrieval or ...
Garda S, Leser U.
europepmc   +4 more sources

Robust Chinese Short Text Entity Disambiguation Method Based on Feature Fusion and Contrastive Learning

Information
To address the limitations of existing methods of short-text entity disambiguation, specifically in terms of their insufficient feature extraction and reliance on massive training samples, we propose an entity disambiguation model called COLBERT, which ...
Qishun Mei, Xuhui Li
doaj   +3 more sources

Chinese Knowledge Based Question Answering Based on Multi-feature Entity Disambiguation [PDF]

Jisuanji gongcheng, 2022
The application of question answering system to the fields of artificial intelligence, natural language processing and information retrieval has got excellent results.Knowledge Based Question Answering(KBQA) is an important part of question answering ...
ZHANG Pengju, JIA Yonghui, CHEN Wenliang
doaj   +1 more source

ExtEnD: Extractive Entity Disambiguation

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
Local models for Entity Disambiguation (ED) have today become extremely powerful, in most part thanks to the advent of large pre-trained language models. However, despite their significant performance achievements, most of these approaches frame ED through classification formulations that have intrinsic limitations, both computationally and from a ...
Barba, Edoardo, Procopio, Luigi, Navigli, Roberto   +2 more
openaire   +2 more sources

Entity Disambiguation with Entity Definitions

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023
Local models have recently attained astounding performances in Entity Disambiguation (ED), with generative and extractive formulations being the most promising research directions. However, previous works limited their studies to using, as the textual representation of each candidate, only its Wikipedia title.
Luigi Procopio, Simone Conia, Edoardo Barba, Roberto Navigli   +3 more
openaire   +2 more sources

Named Entity Disambiguation at Scale [PDF]

, 2020
Named Entity Disambiguation (NED) is a crucial task in many Natural Language Processing applications such as entity linking, record linkage, knowledge base construction, or relation extraction, to name a few. The task in NED is to map textual variations of a named entity to its formal name.
Aghaebrahimian, Ahmad, Cieliebak, Mark
openaire   +1 more source

Entity Linking Method for Chinese Short Text Based on Siamese-Like Network

Information, 2022
Entity linking plays a fundamental role in knowledge engineering and data mining and is the basis of various downstream applications such as content analysis, relationship extraction, question and answer.
Yang Zhang, Jin Liu, Bo Huang, Bei Chen
doaj   +1 more source

Global Entity Disambiguation with BERT

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
We propose a global entity disambiguation (ED) model based on BERT. To capture global contextual information for ED, our model treats not only words but also entities as input tokens, and solves the task by sequentially resolving mentions to their referent entities and using resolved entities as inputs at each step.
Yamada, Ikuya, Washio, Koki, Shindo, Hiroyuki, Matsumoto, Yuji   +3 more
openaire   +2 more sources

An Entity Disambiguation Method Based on Deep Learning

Nantong Daxue xuebao. Ziran kexue ban, 2021
The traditional named entity disambiguation technology usually relies on rich context and knowledge of external entities. However, many emerging entities lack knowledge bases and the text containing entities is short.
WEN Wanzhi; JIANG Wenxuan; GE Wei; ZHU Kai; LI Xikai; WU Xuefei
doaj   +1 more source