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This paper explores the application of Natural Language Processing (NLP) and Large Language Models (LLMs) to analyze financial reports, focusing on the identification of corporate relationships and shareholder structures. The study leverages Retrieval-Augmented Generation (RAG) techniques to enhance the accuracy and efficiency of information extraction, mitigating challenges associated with unstructured data, different document formats, and lack of information. From this work has resulted a complete tool, to retrieve the information and generate the charts and tables.

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CompanyShareH–A Intelligent System to Retrieve Company Shareholders Relationships, Using NLP and LLM’s

  • 会议论文

  • 发表日期：

    2026年

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  • Pedro Filipe Oliveira,
  • Paulo Matos

摘要

This paper explores the application of Natural Language Processing (NLP) and Large Language Models (LLMs) to analyze financial reports, focusing on the identification of corporate relationships and shareholder structures. The study leverages Retrieval-Augmented Generation (RAG) techniques to enhance the accuracy and efficiency of information extraction, mitigating challenges associated with unstructured data, different document formats, and lack of information. From this work has resulted a complete tool, to retrieve the information and generate the charts and tables.