Incorporating contexts to open information extraction
Open Information Extraction (OpenIE) is a critical NLP task that aims to extract structured relational tuples from unstructured open-domain text. The technique well suits many open-world natural language understanding scenarios, such as question answering, knowledge base/graph construction, explicit...
Main Author: | Dong, Kuicai |
---|---|
Other Authors: | Sun Aixin |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/174529 |
Similar Items
-
Design and Construction of a NLP Based Knowledge Extraction Methodology in the Medical Domain Applied to Clinical Information
by: Denis Cedeño Moreno, et al.
Published: (2018-10-01) -
Natural Language Processing for Information Extraction of Gastric Diseases and Its Application in Large-Scale Clinical Research
by: Gyuseon Song, et al.
Published: (2022-05-01) -
Survey on Event Extraction Technology
by: ZHU Yi-na, CAO Yang, ZHONG Jing-yue, ZHENG Yong-zhi
Published: (2022-12-01) -
Context Sensitive Verb Similarity Dataset for Legal Information Extraction
by: Gathika Ratnayaka, et al.
Published: (2022-06-01) -
Diffusion models for natural language processing
by: Hoang, Minh Nhat
Published: (2024)