Deep-change at AXOLOTL-24: Orchestrating WSD and WSI Models for Semantic Change Modeling

TL;DR

This paper presents novel methods for semantic change modeling that effectively distribute word usages across senses over time, achieving state-of-the-art results in the AXOLOTL-24 shared task.

Contribution

It introduces three new methods for semantic change detection and a model to identify usages outside predefined senses, advancing the field of diachronic lexical analysis.

Findings

Achieved state-of-the-art results on AXOLOTL-24 subtask

Developed a model to detect out-of-sense usages

Proposed three novel methods for sense distribution

Abstract

This paper describes our solution of the first subtask from the AXOLOTL-24 shared task on Semantic Change Modeling. The goal of this subtask is to distribute a given set of usages of a polysemous word from a newer time period between senses of this word from an older time period and clusters representing gained senses of this word. We propose and experiment with three new methods solving this task. Our methods achieve SOTA results according to both official metrics of the first substask. Additionally, we develop a model that can tell if a given word usage is not described by any of the provided sense definitions. This model serves as a component in one of our methods, but can potentially be useful on its own.