Method, system and software for resolving conflicts in a set of information

A system for resolving a conflict in a set of unstructured information, the system comprising a central server arranged to identify and store, in one or several databases, in referenced and/or actual format,

• a set of existing information sources;
• a set of existing topics;
• a set of existing associations between pairs of individual ones of the existing information sources and individual ones of the existing topics, the set of existing associations each comprising an associated existing source confidence metric;
• and
• a set of existing pieces of content, each of the set of existing pieces of content being associated with one or several associated ones of the existing topics, each of the set of existing pieces of content also being associated with a respective existing topic confidence metric for each of the one or several associated ones of the existing topics;
• the central server further being arranged to:
• receive a first piece of content, the first piece of content being associated with a first information source, the first information source being an originator or provider of the first piece of content;
• provide a first prompt to a first large language model (LLM) the first prompt being configured to request the first LLM to provide a set of identified topics addressed in the first piece of content;
• receive, in a response from the first LLM, a first piece of response information comprising the set of identified topics;
• and
• to store, in the one or several databases, in referenced or actual format, the first piece of content associated with one or several identified topics in the set of identified topics and, for each of the one or several identified topics in the set of identified topics, a corresponding respective first topic confidence metric for the combination of the first piece of content and the identified topic, wherein
• the central server is further arranged to, for each of the one or several identified topics of the set of identified topics, the identified topic forming part of the set of existing topics, perform the following steps:
• identifying a first subset of the existing pieces of content that are related to the identified topic;
• providing a second prompt to a second LLM, the second LLM being the same as or different from the first LLM, the second prompt being configured to request the second LLM to provide information regarding if the first piece of content supports, contradicts or is neutral in relation to one or several of the first subset of the existing pieces of content;
• receiving, in a response from the second LLM, a second piece of response information indicating that the first piece of content contradicts a particular existing piece of content of the first subset of existing pieces of content;
• and
• determining the first topic confidence metric based on a source confidence metric between the first information source and the identified topic, the first topic confidence metric further being determined based on an existing topic confidence metric for the identified topic and the particular piece of content.

A computer program product, stored on a non-transitory computer readable medium, for resolving a conflict in a set of unstructured information, the computer program product being arranged to, when executing on one or several processors, identifying and store in one or several databases, in referenced and/or actual format,

• a set of existing information sources;
• a set of existing topics;
• a set of existing associations between pairs of individual ones of the existing information sources and individual ones of the existing topics, the set of existing associations each comprising an associated existing source confidence metric;
• and
• a set of existing pieces of content, each of the set of existing pieces of content being associated with one or several associated ones of the existing topics, each of the set of existing pieces of content also being associated with a respective existing topic confidence metric for each of the one or several associated ones of the existing topics;
• the computer program product further being arranged to, when executing on the one or several processors,
• receive a first piece of content, the first piece of content being associated with a first information source, the first information source being an originator or provider of the first piece of content;
• provide a first prompt to a first large language model (LLM), the first prompt being configured to request the first LLM to provide a set of identified topics addressed in the first piece of content;
• receive, in a response from the first LLM, a first piece of response information comprising the set of identified topics;
• and
• store, in the one or several databases, in referenced or actual format, the first piece of content associated with one or several identified topics in the set of identified topics and, for each of the one or several identified topics in the set of identified topics, a corresponding respective first topic confidence metric for the combination of the first piece of content and the identified topic, wherein
• the computer program product further being arranged to, when executing on the one or several processors, for each of the one or several identified topics of the set of identified topics, the identified topic forming part of the set of existing topics, perform the following steps:
• identifying a first subset of the existing pieces of content that are related to the identified topic;
• providing a second prompt to a second LLM, the second LLM being the same as or different from the first LLM, the second prompt being configured to request the second LLM to provide information regarding if the first piece of content supports, contradicts or is neutral in relation to one or several of the first subset of the existing pieces of content;
• receiving, in a response from the second LLM, a second piece of response information indicating that the first piece of content contradicts a particular existing piece of content of the first subset of existing pieces of content;
• and
• determining the first topic confidence metric based on a source confidence metric between the first information source and the identified topic, the first topic confidence metric further being determined based on an existing topic confidence metric for the identified topic and the particular piece of content.