[Purpose/Significance] Identifying technological themes in a given field is crucial for providing decision support for innovation to research management departments and researchers. The technology theme identification based on SAO triplets elevates the results from the word level to the triplet level, enhancing the practicality of theme identification. However, there are still some problems in this method, such as the lack of key technical information, the low granularity of the results and the difficulty in updating triplets. To address these issues, this paper proposes a dynamic completion method for triplets aimed at technology theme identification. [Method/Process] First, SAO triplets were extracted from the abstracts of specific domain literature using OpenIE6. Then, based on BERTopic, the domain SAO triplets were modeled to identify technological theme triplets through their S-A structure, with these triplets serving as the basic unit for representing technological themes. Finally, by constructing appropriate prompts, the GPT-4o model was employed in conjunction with the original abstracts to dynamically complete the technological theme triplets, resulting in triplets with comprehensive semantic information, thus enhancing the granularity and interpretability of the thematic representation. [Result/Conclusion] Based on empirical study conducted on data from the field of high-electron-mobility transistors (HEMTs), the results verify the dynamic updating capability and engineering reliability in terms of dynamic completion of triplets in technical topics within scientific and technological literature, and demonstrate its cross-sentence completion ability.
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