Automatic　acquisition　of　ISA　relations　is　a　basic　problem　in　knowledge　acquisition　from　text.　We　present　an　iterative　method　extracting　ISA　relations　from　large　Chinese　free　text　for　ontology　learning.　Firstly,　it　initially　discovers　a　set　of　sentences　using　several　special　Chinese　lexico-syntactic　patterns　from　free　text　corpus.　Secondly　we　combine　outside　layer　removal　and　inside　layer　gathering　for　acquiring　concepts　of　constituting　ISA　relation.　Finally,　ISA　relations　are　verified　with　multiple　features.　Extracted　ISA　relations　will　be　selected　for　new　relation　extracting　cycle.　Experimental　results　demonstrate　good　performance　of　the　method　for　extracting　ISA　relation　from　large　Chinese　corpus.　©　2010　ACADEMY　PUBLISHER.