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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Библиографические подробности
Главные авторы: Helena Ceovic, Adrian Satja Kurdija, Goran Delac, Marin Silic
Формат: Artigo
Язык:Inglês
Опубликовано: IEEE 2022-01-01
Серии:IEEE Access
Предметы:
Named entity recognition
natural language processing
address entity
BERT
BiLSTM-CRF architecture
Flair
Online-ссылка:https://ieeexplore.ieee.org/document/9757239/
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