Sincet he appearance of the' Semantic Web' andt he developmento f 'RDF'a nd 'OWL', ontologiesg ainedn ew importancei nc omputer science. Ontological structures can be used to make knowledgea vailable to artificial intelligents ystems.B ut such systems need commonsense knowledget os imulate human reasoning beyond theb oundariesg iven by specificd omains.F or this purposec ommonsense ontologiesa re employed.H owever,e xistingc ommonsense ontologies, e.g. Cyc[ Cy10],w erec onstructedo veralengthyp

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... eriodo ft ime. An interestingp roposal to reach this in shortert imew ith less effort is to exposet he structureo fc ommonsense knowledgeb ya nalyzing theu se of wordsi nn atural language.B ased on this,amethod to automatically gain commonsense ontologies with less effort will be presented. Them ainp oint of this method is the automatization. Fort hisp urpose data mining techniques area pplieda nd an algorithm to generate theresultingontologyout of thegaineddataisintroduced. Exposing the structure of commonsense knowledge To avertt he immensee ffort 1 fort he constructiono fcommonsenseo ntologies, therei s need forn ew methods to gain theseo ntological structures.S aba[ Sa07] proposes to expose-andn ot newlyd evelop -t he structureo fc ommonsense knowledge by analyzingt he useo fw ords in naturall anguage. According to this,n atural language shouldguide theprocessofgaining acommonsense ontology. Four steps toward an ontological structure Asking ac hild,i fi tm akes senset os ay 'a dog barks'o r' ab ook barks', oneg etsa n explicit positive or negative answer.O nt hiss impleb ase-thev iewo fachild -t he analysis of words is executed.