Joint entity and relation extraction with part-of-speech-aware attention and dependency parsing embedding

Huaiqian He

doi:10.1117/12.2685463

15 August 2023 Joint entity and relation extraction with part-of-speech-aware attention and dependency parsing embedding

Huaiqian He

Author Affiliations +

Proceedings Volume 12719, Second International Conference on Electronic Information Technology (EIT 2023); 127192Q (2023) https://doi.org/10.1117/12.2685463
Event: Second International Conference on Electronic Information Technology (EIT 2023), 2023, Wuhan, China

Abstract

Joint entity and relation extraction is an important task in natural language processing, whose purpose is to obtain all triples in text. However, the existing models seldom pay attention to the part-of-speech (pos) of each word and the dependency parsing (dp) in the sentence. To solve these problems. a joint extraction model with part-of-speech-aware attention and dependency parsing embedding is proposed, named PADPE. The proposed model obtains better word representation through pos-aware attention mechanism. In addition, the parts of speech and dependency characteristics are integrated respectively in entity classification and relation classification to improve the accuracy of the classifier. The experimental results demonstrate that our model can solve the overlapping triple problem more effectively and outperform other baselines on three public datasets.

Citation Download Citation

Huaiqian He "Joint entity and relation extraction with part-of-speech-aware attention and dependency parsing embedding", Proc. SPIE 12719, Second International Conference on Electronic Information Technology (EIT 2023), 127192Q (15 August 2023); https://doi.org/10.1117/12.2685463

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available