Abstract
At present, research on remote-supervised relationship extraction fail to fully consider the position information among words in a sentence, and the extracted relationship may be inconsistent with the actual relationship. Therefore, this paper combines syntactic dependency tree and ontological constraint to carry out remote-supervised relationship extraction. The syntactic dependency tree is used to obtain the position weight of each word in the sentence and the domain ontology constraint is introduced to improve the accuracy of the extraction relationship. Experiments on Freebase+NYT data set show that this model can effecttively reduce the noise interference of wrong labels, and the model improves the accuracy by 2% compared with other reference models, thus better realizing relation extraction and laying a relevant foundation for the construction of high-precision knowledge map.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
