Medical llm model inference method based on knowledge graph and related devices

An apparatus comprising:

• one or more processors;
• and
• one or more tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more processors, perform operations comprising:
• obtaining target dialogue text entered by a user;
• identifying, from a knowledge graph, a subgraph related to an entity mention comprised in the target dialogue text, wherein the knowledge graph comprises nodes and edges connecting the nodes, the nodes represent entities, and the edges represent relationships between the entities, and the subgraph comprises a target node that represents a target entity and a plurality of neighboring nodes connected to the target node;
• obtaining attribute values of a plurality of attributes of the target entity from multi-turn dialogue text that is entered by the user and that comprises the target dialogue text;
• constructing, based on the subgraph and the attribute values of the plurality of attributes of the target entity, a dialogue graph corresponding to the target dialogue text;
• constructing a prompt based on the dialogue graph and the target dialogue text;
• and
• inputting the prompt into an LLM model, wherein the LLM model performs logical inference based on the prompt.

A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

• obtaining target dialogue text entered by a user;
• identifying, from a knowledge graph, a subgraph related to an entity mention comprised in the target dialogue text, wherein the knowledge graph comprises nodes and edges connecting the nodes, the nodes represent entities, and the edges represent relationships between the entities, and the subgraph comprises a target node that represents a target entity and a plurality of neighboring nodes connected to the target node;
• obtaining attribute values of a plurality of attributes of the target entity from multi-turn dialogue text that is entered by the user and that comprises the target dialogue text;
• constructing, based on the subgraph and the attribute values of the plurality of attributes of the target entity, a dialogue graph corresponding to the target dialogue text;
• constructing a prompt based on the dialogue graph and the target dialogue text;
• and
• inputting the prompt into an LLM model, wherein the LLM model performs logical inference based on the prompt.