▁the ▁S ense val / Sem E val ▁compet itions ▁parts ▁of ▁speech ▁are ▁provided ▁as ▁input ▁for ▁the ▁text ▁to ▁dis ambigu ate ). ▁ ▁It ▁is ▁instruct ive ▁to ▁compare ▁the ▁word ▁sense ▁dis ambiguation ▁problem ▁with ▁the ▁problem ▁of ▁part - of - spe ech ▁tag ging . ▁Both ▁involve ▁dis ambigu ating ▁or ▁tag ging ▁with ▁words , ▁be ▁it ▁with ▁sens es ▁or ▁parts ▁of ▁speech . ▁However , ▁algorithms ▁used ▁for ▁one ▁do ▁not ▁tend ▁to ▁work ▁well ▁for ▁the ▁other , ▁mainly ▁because ▁the ▁part ▁of ▁speech ▁of ▁a ▁word ▁is ▁primarily ▁determined ▁by ▁the ▁immediately ▁adjacent ▁one ▁to ▁three ▁words , ▁whereas ▁the ▁sense ▁of ▁a ▁word ▁may ▁be ▁determined ▁by ▁words ▁further ▁away . ▁The ▁success ▁rate ▁for ▁part - of - spe ech ▁tag ging ▁algorithms ▁is ▁at ▁present ▁much ▁higher ▁than ▁that ▁for ▁W SD , ▁state - of - the ▁art ▁being ▁around ▁ 9 5 % ▁accuracy ▁or ▁better , ▁as ▁compared ▁to ▁less ▁than ▁ 7 5 % ▁accuracy ▁in ▁word ▁sense ▁dis ambiguation ▁with ▁super vised ▁learning . ▁These ▁figures ▁are ▁typical ▁for ▁English , ▁and ▁may ▁be ▁very ▁different ▁from ▁those ▁for ▁other ▁languages . ▁ ▁Inter - jud ge ▁variance ▁Another ▁problem ▁is ▁inter - jud ge ▁variance . ▁W SD ▁systems ▁are ▁normally ▁tested ▁by ▁having ▁their ▁results ▁on ▁a ▁task ▁compared ▁against ▁those ▁of ▁a ▁human . ▁However , ▁while ▁it ▁is ▁relatively ▁easy ▁to ▁assign ▁parts ▁of ▁speech ▁to ▁text , ▁training ▁people