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...

Täydet tiedot

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Bibliografiset tiedot
Päätekijät: Helena Ceovic, Adrian Satja Kurdija, Goran Delac, Marin Silic
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: IEEE 2022-01-01
Sarja:IEEE Access
Aiheet:
Named entity recognition
natural language processing
address entity
BERT
BiLSTM-CRF architecture
Flair
Linkit:https://ieeexplore.ieee.org/document/9757239/
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