  This study addresses the task of Unknown Sense Detection in English and
Swedish. The primary objective of this task is to determine whether the meaning
of a particular word usage is documented in a dictionary or not. For this
purpose, sense entries are compared with word usages from modern and historical
corpora using a pre-trained Word-in-Context embedder that allows us to model
this task in a few-shot scenario. Additionally, we use human annotations to
adapt and evaluate our models. Compared to a random sample from a corpus, our
model is able to considerably increase the detected number of word usages with
non-recorded senses.
