Palantir Technologies Inc.

Johannes Beil

Nicolas Prettejohn

Paul Baseotto

Lauren Brown

Elliot Hirsch

Anirvan Mukherjee

Michael Zullo

Jessica Winssinger

Rushad Heerjee

Edgar Gomes De Araujo

Shubhankar Sachdev

Craig De Souza

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.

Language model-based data object extraction and visualization

A fuzzy matching system matching data records in one or more data sets based on user-customized selection of multiple fuzzy matching algorithms. Possible matches may be displayed to a user, who provides feedback on the accuracy of the matches, which may then be used by a machine learning algorithm to update weightings and parameters of the multiple fuzzy matching algorithms, such as based on machine learning analysis of the matching results and the user feedback.

Entity matching with machine learning fuzzy logic

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Copenhagen, Denmark

Johannes Beil