▁computational ▁lingu istics , ▁word - s ense ▁dis ambiguation ▁( W SD ) ▁is ▁an ▁open ▁problem ▁concerned ▁with ▁ident ifying ▁which ▁sense ▁of ▁a ▁word ▁is ▁used ▁in ▁a ▁sentence . ▁The ▁solution ▁to ▁this ▁problem ▁impact s ▁other ▁computer - related ▁writing , ▁such ▁as ▁disc ourse , ▁impro ving ▁relev ance ▁of ▁search ▁engines , ▁an ap hora ▁resolution , ▁coh er ence , ▁and ▁inference . ▁ ▁The ▁human ▁brain ▁is ▁quite ▁prof ic ient ▁at ▁word - s ense ▁dis ambiguation . ▁That ▁natural ▁language ▁is ▁formed ▁in ▁a ▁way ▁that ▁requires ▁so ▁much ▁of ▁it ▁is ▁a ▁reflection ▁of ▁that ▁ne uro logic ▁reality . ▁In ▁other ▁words , ▁human ▁language ▁developed ▁in ▁a ▁way ▁that ▁reflect s ▁( and ▁also ▁has ▁helped ▁to ▁shape ) ▁the ▁inn ate ▁ability ▁provided ▁by ▁the ▁brain ' s ▁neural ▁networks . ▁In ▁computer ▁science ▁and ▁the ▁information ▁technology ▁that ▁it ▁enables , ▁it ▁has ▁been ▁a ▁long - term ▁challenge ▁to ▁develop ▁the ▁ability ▁in ▁computers ▁to ▁do ▁natural ▁language ▁processing ▁and ▁machine ▁learning . ▁ ▁A ▁rich ▁variety ▁of ▁techniques ▁have ▁been ▁research ed , ▁from ▁dictionary - based ▁methods ▁that ▁use ▁the ▁knowledge ▁encoded ▁in ▁lex ical ▁resources , ▁to ▁super vised ▁machine ▁learning ▁methods ▁in ▁which ▁a ▁class ifier ▁is ▁trained ▁for ▁each ▁distinct ▁word ▁on ▁a ▁cor pus ▁of ▁manually ▁sense - annot ated ▁examples , ▁to ▁completely ▁un super vised ▁methods ▁that ▁cluster ▁occurr ences ▁of ▁words , ▁thereby ▁indu cing ▁word ▁sens