Detection of Non-recorded Word Senses in English and Swedish

Jonathan Lautenschlager, Emma Sköldberg, Simon Hengchen, Dominik Schlechtweg
3/4/2024
cs.CL

No official code found. Best implementation: iguanodon-ai/SO-extract-db (1 star, CC-BY-SA-4.0, last commit 2026-04-07).

Abstract

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 on the target corpora to adapt hyperparameters and evaluate our models using 5-fold cross-validation. 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.

View on arXivView PDF

Code Implementations(1)

iguanodon-ai/SO-extract-dbCommunity100%
CC-BY-SA-4.0
10Python, DockerfileNov 7, 20226 months agoCC-BY-SA-4.0

Similar Papers

Presence or Absence: Are Unknown Word Usages in Dictionaries?

81% match1 repo12024

How Well Do Large Language Models Disambiguate Swedish Words?

80% match2024

What do Language Models know about word senses? Zero-Shot WSD with Language Models and Domain Inventories

77% match2023

Solving Word-Sense Disambiguation and Word-Sense Induction with Dictionary Examples

77% match2025

Word sense extension

77% match1 repo82023

A Survey on Lexical Ambiguity Detection and Word Sense Disambiguation

76% match2024

Cite this paper

@article{lautenschlager2024detection,
  title  = {Detection of Non-recorded Word Senses in English and Swedish},
  author = {Jonathan Lautenschlager and Emma Sköldberg and Simon Hengchen and Dominik Schlechtweg},
  year   = {2024},
  eprint = {2403.02285},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.02285v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2403.02285.svg)](https://codeofpaper.com/paper/2403.02285)

Discussion