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The Private Equity (PE) firms operate investment funds by acquiring andmanaging companies to achieve a high return upon selling. Many PE funds arethematic, meaning investment professionals aim to identify trends by coveringas many industry sectors as possible, and picking promising companies withinthese sectors. So, inferring sectors for companies is critical to the successof thematic PE funds. In this work, we standardize the sector framework anddiscuss the typical challenges; we then introduce our sector inference systemaddressing these challenges. Specifically, our system is built on amedium-sized generative language model, finetuned with a prompt + model tuningprocedure. The deployed model demonstrates a superior performance than thecommon baselines. The system has been serving many PE professionals for over ayear, showing great scalability to data volume and adaptability to any changein sector framework and/or annotation.

A Scalable and Adaptive System to Infer the Industry Sectors of Companies: Prompt + Model Tuning of Generative Language Models