Entity analysis system

A computer-implemented method of learning related entities, the method comprising:

• receiving a plurality of entities, each entity among the plurality of entities relating to a first concept;
• receiving training content including the plurality of entities;
• and
• learning additional entities that are related to the first concept by iteratively performing the following steps:
• identifying one or more potential word templates from the training content based on occurrences of one or more words in the training content relating to the first concept;
• identifying one or more word templates from the one or more potential word templates based on a frequency of occurrence of the one or more potential word templates and based on one or more part-of-speech tags of the one or more potential word templates;
• adding the one or more identified word templates to a set of word templates;
• generating, for each identified word template, a confidence score for the identified word template based on a frequency of occurrence of the identified word template;
• and
• adjusting, for each identified word template, the confidence score of the identified word template based on whether the one or more part of speech tags of the identified word template is similar to part-of-speech tags of word templates of the set of word templates.

A computer-implemented method of learning related entities, the method comprising:

• receiving a plurality of entities, each entity among the plurality of entities relating to a first concept;
• receiving training content including the plurality of entities;
• and
• learning additional entities that are related to the first concept by iteratively performing the following steps:
• identifying one or more potential word templates from the training content based on occurrences of one or more words in the training content relating to the first concept;
• adding the one or more identified word templates to a set of word templates;
• and
• adjusting, for each identified word template, a confidence score of the identified word template when one or more part of speech tags of the identified word template is similar to part-of-speech tags of word templates of the set of word templates.

A computer product for learning related entities, the computer product comprising a non-transitory computer-readable medium containing computer program code for performing a method comprising:

• receiving a plurality of entities, each entity among the plurality of entities relating to a first concept;
• receiving training content including the plurality of entities;
• and
• learning additional entities that are related to the first concept by iteratively performing the following steps:
• identifying one or more word templates from the training content based on occurrences of one or more words in the training content;
• adding the one or more identified word templates to a set of word templates;
• generating, for each identified word template, a confidence score for the identified word template based on a frequency of occurrence of the identified word template;
• and
• adjusting, for each identified word template, the confidence score of the identified word template based on whether one or more part of speech tags of the identified word template is similar to part-of-speech tags of word templates of the set of word templates.

The computer product of claim 40, wherein learning additional entities that are related to the first concept further comprises:

• adjusting, for each identified word template, the confidence score of the identified word template when the identified word template is identified as being a false positive;
• identifying one or more candidate entities that relate to the first concept based on occurrences of each of the one or more candidate entities in the training content with at least one of the word templates of the set of word templates, wherein the one or more identified candidate entities are added to a set of candidate entities;
• identifying a part-of-speech tag for each candidate entity;
• and
• removing a candidate entity from the set of candidate entities when the part-of-speech tag of the candidate entity is different from a part-of-speech tag of the set of entities,
• wherein the computer product of claim 60 further comprises:
• adding the one or more candidate entities of the set of candidate entities to the set of entities.