Deep-change at AXOLOTL-24: Orchestrating WSD and WSI Models for Semantic Change Modeling
This work addresses semantic change modeling for computational linguistics, but it is incremental as it builds on existing shared task frameworks.
The authors tackled the problem of distributing word usages from a newer time period between historical senses and newly gained senses, achieving state-of-the-art results on the AXOLOTL-24 shared task metrics.
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.