Lexical ambiguity detection in professional discourse

作者：

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.

摘要

•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.

论文关键词：Professional discourse,Specialist terminology,Lexical ambiguity,Word embeddings

论文评审过程：Received 28 February 2022, Revised 20 May 2022, Accepted 16 June 2022, Available online 6 July 2022, Version of Record 6 July 2022.

论文官网地址：https://doi.org/10.1016/j.ipm.2022.103000