Work

Assessing the standard-essentiality of 5G technology patents by means of generative artificial intelligence

Year: 2025

Type: article

Abstract: In telecommunication technology, identifying standard-essential patents (SEPs) plays a crucial role in the management of intellectual property. This technology is regulated by technical standards that are largely based on the content of SEPs. These patents are declared standard-essential by their owners because they contain elements of a technical standard. The declaration process leaves room for over- and under-declaration, which entails risks for organizations. This paper focuses on the question of how generative artificial intelligence can be used to assess the standard-essentiality of 5G technology patents. For this purpose, the standard-essentiality is assessed using different prompts with four Large Language Models (LLMs) in two variants. In the first variant, the LLM results are generated by a rather simple prompt and compared with an approach based on unsupervised and supervised machine learning. The result shows that large LLMs are capable of assessing the standard-essentiality. In the second variant, the best-performing LLM is selected and the prompt is expanded to include selected parts of a technical standard. While the assessment results remain largely the same, the LLM is now able to explain in which detail a patent is part of a standard. This has several implications for patent evaluation, licensing and litigation strategies.

Source: World Patent Information

DOI: 10.1016/j.wpi.2025.102363

Author: Andre Herzberg

Institution: University of Bremen

Language: English

Topic: Intellectual Property and Patents

Subfield: Management of Technology and Innovation

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,653