Abstract: Various methods and processes, apparatuses or systems, and media for performing a plurality of communications with a knowledge graph by a knowledge graph configured large language model (KGLLM) for answering a question are disclosed. The present disclosure provides receiving, at the KGLLM, the question; generating, by the KGLLM, a plurality of logical reasoning steps based on the received question; identifying and inputting, to the KGLLM, the knowledge graph based on the received question; for each of the plurality of logical reasoning steps: generating a prompt for a logical reasoning step, connecting to the knowledge graph, and retrieving corresponding pieces of information from the knowledge graph based on the generated prompt; and combining the pieces of information retrieved for deriving an answer to the question.

Abstract: A method and a system for determining similarities between entities are provided. The method includes: receiving a request to determine an estimate for a first instrument; generating a query to identify corresponding first data sources that contain data about an entity; identifying, using the generated query, the corresponding first data sources from a system of computer networks; filtering the corresponding first data sources in order to determine at least one primary data source; extracting corresponding first information that relates to the respective entity from the at least one primary data source; identifying, using a large language model, corresponding entity-specific information based on the extracted corresponding first information; comparing the entity-specific information of a first entity with entity-specific information for a plurality of entities; and generating a similarity ranking that list each respective entity from among the plurality of entities in relation to the first entity.

Abstract: A method and a system for automatically processing financial documents to generate knowledge graphs that convey information relating to entities of interest and relationships between those entities are provided. The method includes: receiving a document; extracting raw text included in the document; identifying, based on the extracted raw text, a set of entities that are named in the document; determining respective relationship information that corresponds to respective pairs of entities; constructing a knowledge graph that illustrates respective relationships among the respective pairs of entities; and outputting the knowledge graph. The determination of the respective relationship information may be performed by applying an artificial intelligence (AI) algorithm that is trained by using historical data that relates to the set of entities.

Abstract: A method and a system for automatically processing financial documents to generate knowledge graphs that convey information relating to entities of interest and relationships between those entities are provided. The method includes: receiving a document; extracting raw text included in the document; identifying, based on the extracted raw text, a set of entities that are named in the document; determining respective relationship information that corresponds to respective pairs of entities; constructing a knowledge graph that illustrates respective relationships among the respective pairs of entities; and outputting the knowledge graph. The determination of the respective relationship information may be performed by applying an artificial intelligence (AI) algorithm that is trained by using historical data that relates to the set of entities.