Named Entity Recognition for Addresses: An Empirical Study

In this paper, several model architectures are explored in order to design a high-performing named entity recognition model for addresses which deals with challenges such as diversity, ambiguity and complexity of the address entity. Different types of neural networks are used for training the classi...

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Bibliografiske detaljer

Principais autores:	Helena Ceovic, Adrian Satja Kurdija, Goran Delac, Marin Silic
Format:	Artigo
Sprog:	Inglês
Udgivet:	IEEE 2022-01-01
Serier:	IEEE Access
Fag:	Named entity recognition natural language processing address entity BERT BiLSTM-CRF architecture Flair
Online adgang:	https://ieeexplore.ieee.org/document/9757239/
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