DOAJ Open Access 2021

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

Yuan Huang Zhixing Li Wei Deng Guoyin Wang Zhimin Lin

Abstrak

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.

Topik & Kata Kunci

Computational linguistics. Natural language processing Computer software

Penulis (5)

Yuan Huang

Zhixing Li

Wei Deng

Guoyin Wang

Zhimin Lin

Format Sitasi

APA MLA BibTeX

Huang, Y., Li, Z., Deng, W., Wang, G., Lin, Z. (2021). D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction. https://doi.org/10.1049/cit2.12033

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →

Lihat di Sumber doi.org/10.1049/cit2.12033

Informasi Jurnal

Tahun Terbit: 2021
Sumber Database: DOAJ
DOI: 10.1049/cit2.12033
Akses: Open Access ✓