The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 08, 2025

Filed:

Nov. 29, 2021
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Jun Wang, Jersey City, NJ (US);

Sudipta Sengupta, Sammamish, WA (US);

Zhiguo Wang, Syosset, NY (US);

Ramesh M Nallapati, Fremont, CA (US);

Bing Xiang, Mount Kisco, NY (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/295 (2020.01); G06F 16/2452 (2019.01); G06F 16/2458 (2019.01); G06F 40/284 (2020.01);
U.S. Cl.
CPC ...
G06F 40/295 (2020.01); G06F 16/24522 (2019.01); G06F 16/2468 (2019.01); G06F 40/284 (2020.01);
Abstract

A schema and cell value aware Named Entity Recognition (NER) model is used to perform natural language queries. Natural language queries may be received via an interface of a natural language query processing system. A fuzzy search may be performed that allows non-exact matches for column names or cell values of data sets potentially used to answer the natural language query. An NER model that adds a type embedding for an exact match of a column name or cell found in the fuzzy search that corresponds to a span of one or more words may be applied as part of generating the entity prediction for the natural language query. One or more queries to at least one of the data sets may be performed to return a result to the natural language query using the entity prediction generated by the NER machine learning model.


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