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An End-to-End Method for Joint Extraction of Tibetan Entity Relations
- Source :
- Journal of Computer and Communications. :132-142
- Publication Year :
- 2021
- Publisher :
- Scientific Research Publishing, Inc., 2021.
-
Abstract
- Entity relation extraction is to find entities and relations from unstructured texts, which is beneficial to the applications of knowledge graphs and question answering systems. The traditional methods handle this task in a pipelined manner which extracts the entities first and then recognizes their relations. This framework may lead to error delivery. In order to tackle this problem, this paper proposes an end-to-end method for joint extraction of Tibetan entity relations which can extract entities and relations at the same time. According to the Tibetan spelling characteristics, this paper processes the Tibetan corpus by word-level and character-level respectively. Combined with part of speech tagging, we use the end-to-end model to convert the entity relation extraction task to the tagging problem. Finally, the experimental results show that the proposed method is better than the baseline.
- Subjects :
- business.industry
Computer science
General Medicine
computer.software_genre
Spelling
Task (project management)
End-to-end principle
Knowledge graph
Question answering
Artificial intelligence
Baseline (configuration management)
business
Joint (audio engineering)
computer
Natural language processing
Entity relation extraction
Subjects
Details
- ISSN :
- 23275227 and 23275219
- Database :
- OpenAIRE
- Journal :
- Journal of Computer and Communications
- Accession number :
- edsair.doi...........89ef2eddb53ac4a913d4efa212808803