Lexical ambiguity detection in professional discourse

Yang Liu, Alan Medlar, Dorota Glowacka

Abstract: Highlights•Lexically ambiguous terms in professional discourse can confuse non-specialists.•Semantic shift methods perform poorly due to noisy terms and data set biases.•We present three case studies in law, statistics and medicine.•Our method has high precision and ranks terms consistently with semantic shift.•The ranking of short phrases reflects their increased specificity.