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.
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