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:
Mar. 04, 2025

Filed:

May. 06, 2022
Applicant:

Sap SE, Walldorf, DE;

Inventor:

Hans-Martin Ramsl, Mannheim, DE;

Assignee:

SAP SE, Walldorf, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/295 (2020.01); G06F 40/253 (2020.01); G06N 3/042 (2023.01); G06N 3/08 (2023.01); G06N 5/022 (2023.01);
U.S. Cl.
CPC ...
G06F 40/295 (2020.01); G06F 40/253 (2020.01); G06N 3/042 (2023.01); G06N 3/08 (2013.01); G06N 5/022 (2013.01);
Abstract

Example methods and systems are directed to generating knowledge graph entities from text. Natural language text is received as input and processed using named entity recognition (NER), part of speech (POS) recognition, and business object recognition (BOR). The outputs of the NER, POS, and BOR processes are combined to generate knowledge entity triples comprising two entities and a relationship between them. Keywords are extracted from the text using NER to generate a set of entities. A node in a knowledge graph is created for at least some of the entities. A POS tagger identifies verbs in the text, generating a set of verbs. Relational verbs (e.g., 'talk to' or “communicated with”) are detected and used to create edges in the knowledge graph. The knowledge graph may be converted back to natural language text using a trained machine learning model.


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