公开(公告)号：US20250077848A1

公开(公告)日：2025-03-06

申请号：US18817793

申请日：2024-08-28

Applicant: NEC Laboratories America, Inc.

Inventor： Xujiang Zhao ,  Haoyu Wang ,  Zhengzhang Chen ,  Wei Cheng ,  Haifeng Chen ,  Yanchi Liu ,  Chen Ling

IPC: G06N3/0475 ,  G16H80/00

Abstract: Systems and methods for a demonstration uncertainty-based artificial intelligence model for open information extraction. A large language model (LLM) can generate initial structured sentences using an initial prompt for a domain-specific instruction extracted from an unstructured text input. Structural similarities between the initial structured sentences and sentences from a training dataset can be determined to obtain structurally similar sentences. The LLM can identify relational triplets from combinations of tokens from generated sentences using and the structurally similar sentences. The relational triplets can be filtered based on a calculated demonstration uncertainty to obtain a filtered triplet list. A domain-specific task can be performed using the filtered triplet list to assist the decision-making process of a decision-making entity.