D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction

Abstract Relation extraction between entity pairs is an increasingly critical area in natural language processing. Recently, the pre‐trained bidirectional encoder representation from transformer (BERT) performs excellently on the text classification or sequence labelling tasks. Here, the high‐level...

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Autores principales:	Yuan Huang, Zhixing Li, Wei Deng, Guoyin Wang, Zhimin Lin
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Computational linguistics. Natural language processing P98-98.5 Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/0249608298f5411d806f6feb296e511b
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spelling	oai:doaj.org-article:0249608298f5411d806f6feb296e511b2021-11-17T03:12:43ZD‐BERT: Incorporating dependency‐based attention into BERT for relation extraction2468-232210.1049/cit2.12033https://doaj.org/article/0249608298f5411d806f6feb296e511b2021-12-01T00:00:00Zhttps://doi.org/10.1049/cit2.12033https://doaj.org/toc/2468-2322Abstract Relation extraction between entity pairs is an increasingly critical area in natural language processing. Recently, the pre‐trained bidirectional encoder representation from transformer (BERT) performs excellently on the text classification or sequence labelling tasks. Here, the high‐level syntactic features that consider the dependency between each word and the target entities into the pre‐trained language models are incorporated. Our model also utilizes the intermediate layers of BERT to acquire different levels of semantic information and designs multi‐granularity features for final relation classification. Our model offers a momentous improvement over the published methods for the relation extraction on the widely used data sets.Yuan HuangZhixing LiWei DengGuoyin WangZhimin LinWileyarticleComputational linguistics. Natural language processingP98-98.5Computer softwareQA76.75-76.765ENCAAI Transactions on Intelligence Technology, Vol 6, Iss 4, Pp 417-425 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computational linguistics. Natural language processing P98-98.5 Computer software QA76.75-76.765
spellingShingle	Computational linguistics. Natural language processing P98-98.5 Computer software QA76.75-76.765 Yuan Huang Zhixing Li Wei Deng Guoyin Wang Zhimin Lin D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction
description	Abstract Relation extraction between entity pairs is an increasingly critical area in natural language processing. Recently, the pre‐trained bidirectional encoder representation from transformer (BERT) performs excellently on the text classification or sequence labelling tasks. Here, the high‐level syntactic features that consider the dependency between each word and the target entities into the pre‐trained language models are incorporated. Our model also utilizes the intermediate layers of BERT to acquire different levels of semantic information and designs multi‐granularity features for final relation classification. Our model offers a momentous improvement over the published methods for the relation extraction on the widely used data sets.
format	article
author	Yuan Huang Zhixing Li Wei Deng Guoyin Wang Zhimin Lin
author_facet	Yuan Huang Zhixing Li Wei Deng Guoyin Wang Zhimin Lin
author_sort	Yuan Huang
title	D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction
title_short	D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction
title_full	D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction
title_fullStr	D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction
title_full_unstemmed	D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction
title_sort	d‐bert: incorporating dependency‐based attention into bert for relation extraction
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/0249608298f5411d806f6feb296e511b
work_keys_str_mv	AT yuanhuang dbertincorporatingdependencybasedattentionintobertforrelationextraction AT zhixingli dbertincorporatingdependencybasedattentionintobertforrelationextraction AT weideng dbertincorporatingdependencybasedattentionintobertforrelationextraction AT guoyinwang dbertincorporatingdependencybasedattentionintobertforrelationextraction AT zhiminlin dbertincorporatingdependencybasedattentionintobertforrelationextraction
_version_	1718425967071854592

D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction

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