System for extracting semantic triples for building a knowledge base

Abstract

The present disclosure relates to a computer-implemented method of generating a semantic triple for building a knowledge base to include data patterns associated with semantic triples derived from unstructured text. The method comprises: providing a sentence associated with unstructured text including a main verb and a taxonomic verb, the taxonomic verb describing a taxonomic relationship; generating a first frame including a first subject, a first relation, and a first object, the first relation including the main verb, wherein the first subject and the first object each include a phrase including one or more sub-strings; generating a second frame including a second subject, a second relation, and a second object, the second relation including the taxonomic verb, wherein the second subject and the second object each include a phrase including one or more sub-strings; identifying a common sub-string in the first subject and either the second subject or the second object, or a common sub-string in the first object and either the second subject or the second object; generating a semantic triple using the first frame and replacing the first subject or the first object having the common sub-string with the second subject or the second object having the common sub-string; and transmitting the semantic triple for inclusion as a data pattern in the knowledge base.

Description

Technical field [0001] The embodiments described herein relate to methods and systems for building a knowledge base (KB) that defines an ontology. Background technique [0002] KB has been created for semantic annotation of documents (text or image), semantic search, reasoning, automatic diagnosis, dialogue systems, and many other knowledge-based applications. KB includes the relationship between multiple concepts and link concepts. It is usually created manually by domain experts, but this can be laborious, time-consuming, and costly. Alternatively, it can also be constructed automatically (semi-automatically) by entering text, recognizing sentences in the text, deriving semantic triples from the sentences, and then storing these triples or linking them to an existing KB. In this way, KB can be created and expanded. [0003] The purpose of this disclosure is to improve the prior art. In particular, the present disclosure solves a technical problem related to computer technolog...

AI Technical Summary

Problems solved by technology

It is usually created manually by domain experts, but this can be laborious, time-consuming and costly

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