US 12,189,782 B2
Methods and systems for natural language processing of graph database queries
Christine M. Difonzo, Rockville, MD (US); and Steven E. Noel, Woodbridge, VA (US)
Assigned to The MITRE Corporation, McLean, VA (US)
Filed by The MITRE Corporation, McLean, VA (US)
Filed on Dec. 6, 2021, as Appl. No. 17/543,184.
Claims priority of provisional application 63/214,164, filed on Jun. 23, 2021.
Prior Publication US 2022/0414228 A1, Dec. 29, 2022
Int. Cl. G06F 21/57 (2013.01); G06F 16/2452 (2019.01); G06F 16/901 (2019.01); G06F 16/9032 (2019.01); G06F 40/169 (2020.01); G06F 40/295 (2020.01); G06F 21/55 (2013.01)
CPC G06F 21/577 (2013.01) [G06F 16/24522 (2019.01); G06F 16/9024 (2019.01); G06F 16/90332 (2019.01); G06F 40/169 (2020.01); G06F 40/295 (2020.01); G06F 21/552 (2013.01); G06F 2221/034 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for translating a natural language user query into a graph database query comprising:
receiving a first input from a user comprising a natural language query regarding data in a graph database;
processing the natural language query using a named entity recognition (NER) machine learning model to extract named entities from the natural language query and tag them according to an entity type;
processing the tagged named entities using a word similarity algorithm to identify corresponding nodes and edges, and their associated properties, in the graph database;
processing the natural language query using an intent classification machine learning model to determine a user intent for the natural language query; and
applying a user intent-based template to the identified nodes and edges to formulate a graph database query that corresponds to the natural language query.