Palantir technologies inc. (20240354322). LANGUAGE MODEL-BASED DATA OBJECT EXTRACTION AND VISUALIZATION simplified abstract

LANGUAGE MODEL-BASED DATA OBJECT EXTRACTION AND VISUALIZATION

Organization Name

palantir technologies inc.

Inventor(s)

Anirvan Mukherjee of Brooklyn NY (US)

Craig De Souza of Jersey City NJ (US)

Edgar Gomes De Araujo of Sao Paulo (BR)

Johannes Beil of Copenhagen (DK)

Jessica Winssinger of New York NY (US)

Michael Zullo of Scarsdale NY (US)

Rushad Heerjee of New York NY (US)

Shubhankar Sachdev of New York NY (US)

LANGUAGE MODEL-BASED DATA OBJECT EXTRACTION AND VISUALIZATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240354322 titled 'LANGUAGE MODEL-BASED DATA OBJECT EXTRACTION AND VISUALIZATION

The abstract of the patent application describes computer-implemented systems and methods that utilize language models for generating data objects and updating an ontology.

• Large language models (LLMs) are used to generate data triples and classified triples.
• A similarity search is executed with the classified triple to match data object types in the ontology.
• Data objects representing entities in the data triple are added to a database based on the ontology match.

Potential Applications: - Natural language processing - Data modeling and ontology management - Knowledge graph construction

Problems Solved: - Automating the generation and classification of data objects - Streamlining ontology updates and maintenance

Benefits: - Improved efficiency in data processing - Enhanced accuracy in ontology management - Facilitates semantic understanding in data analysis

Commercial Applications: Title: Semantic Data Processing Solutions This technology can be applied in industries such as: - E-commerce for product recommendation systems - Healthcare for patient data management - Finance for fraud detection algorithms

Frequently Updated Research: Stay updated on advancements in natural language processing and ontology modeling for enhanced data processing capabilities.

Questions about Semantic Data Processing Solutions: 1. How does this technology improve data processing efficiency?

  - By utilizing large language models to automate data object generation and ontology updates.

2. What are the potential applications of this technology in different industries?

  - This technology can be applied in various sectors for data management and analysis.

Original Abstract Submitted

computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for generating data objects and/or updating an ontology. a computer-implemented method may include: employing one or more large language models (“llms”) to generate at least a data triple and a classified triple; executing, using the classified triple, a similarity search with reference to an ontology to determine that the classified triple at least partially matches one or more data object types defined in the ontology; in response to the determination, adding into a first database at least a first data object of a first data object type that represents a first entity in the data triple and a second data object of a second data object type that represents a second entity in the data triple.