Language-independent information extraction based on formal concept analysis

This paper proposes application of Formal Concept Analysis (FCA) in creating character-level information extraction patterns and presents BigGrams: a prototype of a language-independent information extraction system. The main goal of the system is to recognise and to extract of named entities belonging to some semantic classes (e.g. cars, actors, pop-stars, etc.) from semi structured text (web page documents).