International Business Machines Corporation
Natural language interface databases
Last updated:
Abstract:
Embodiments are disclosed for correcting a natural language interface database (NLIDB) system. The techniques include receiving feedback indicating that an answer provided in response to a question for an NLIDB system is inaccurate. The techniques further include finding an ontology element for a datastore of the NLIDB system that matches to the feedback. The techniques also include selecting candidate annotations for the NLIDB system based on the ontology element and a data type of the ontology element. Additionally, the techniques include generating a question-answer (QA) pair for each of the candidate annotations. Further, the techniques include adding one of the candidate annotations to annotations for a natural language query (NLQ) engine of the NLIDB system based on a client verification of the QA pair.
Utility
24 Apr 2019
14 Dec 2021