eCite Digital Repository
Adding an inception network to neural network open information extraction
Citation
Le, DV and Kirkby, K and Montgomery, J and Scanlan, J, Adding an inception network to neural network open information extraction, IEEE Intelligent Systems ISSN 1541-1672 (2022) [Refereed Article]
![]() | PDF Pending copyright assessment - Request a copy 2Mb |
DOI: doi:10.1109/MIS.2022.3168265
Abstract
This paper presents a method to resolve tuples from plain text by adding an inception network, and dependency path embedding to existing neural network methods of Open Information Extraction (Open IE). Inception networks are used in analysis of computer vision, and dependency path embedding in text processing, but neither has been reported with Open IE. Performance was measured on benchmark datasets using two existing Open IE deep learning methods, one using bidirectional long short-term memory and BIO tagging (RnnOIE-verb), and another using a span-based model (SpanOIE). RnnOIE-verb was compared with RnnOIE-verb plus inception network and/or dependency path embedding. SpanOIE was compared with SpanOIE plus inception network. Performance slightly increased with the addition of inception network to RnnOIE-verb (before AUC 0.45, F1 0.59; after AUC 0.46, F1 0.60) and inception network to SpanOIE (before AUC 0.63, F1 0.748; after AUC 0.64, F1 0.764). The performance gain was minor but potentially relevant to an iterative process of improvement.
Item Details
Item Type: | Refereed Article |
---|---|
Keywords: | natural language processing, open information extraction, neural networks, inception network, predictive models |
Research Division: | Information and Computing Sciences |
Research Group: | Artificial intelligence |
Research Field: | Natural language processing |
Objective Division: | Information and Communication Services |
Objective Group: | Information systems, technologies and services |
Objective Field: | Artificial intelligence |
UTAS Author: | Le, DV (Mr Van Duy Le) |
UTAS Author: | Kirkby, K (Professor Kenneth Kirkby) |
UTAS Author: | Montgomery, J (Dr James Montgomery) |
UTAS Author: | Scanlan, J (Dr Joel Scanlan) |
ID Code: | 149876 |
Year Published: | 2022 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2022-04-21 |
Last Modified: | 2022-06-09 |
Downloads: | 0 |
Repository Staff Only: item control page