The platform detects brands, organizations, locations and persons.
Neticle can recognize the following entities: brands, organizations, locations and people. The former three work the same way as automatic label recognition does: each brand, organization and location has its own corresponding synonym set. These entities are recognized if any of their synonyms can be found in the text, by matching the beginning of a phrase, or by exact match (depending on the settings of each entity). Some entities can have excluded phrases as well, this prevents entity recognition in texts where the excluded phrases are present.
For example, the brand MOL has only one synonym: mol. It uses the exact match method, which means it will only be a hit if the text contains the word mol, this three-character string as it is. This way we can be sure it will not be a hit for words like molecule, Molotov etc. without using any excluded phrases.
The name (people) recognition in texts uses a more dynamic method: the system has access to lists of existing given names and surnames and it tries to find their possible combinations in each verbatim.