Related papers: TartuNLP @ AXOLOTL-24: Leveraging Classifier Output for New Sense Detection in Lexical Semantics

TartuNLP @ AXOLOTL-24: Leveraging Classifier Output for New Sense Detection in Lexical Semantics

URL: http://arxiv.org/abs/2407.03861v1
Date: Thu, 4 Jul 2024 11:46:39 GMT
Title: TartuNLP @ AXOLOTL-24: Leveraging Classifier Output for New Sense Detection in Lexical Semantics
Authors: Aleksei Dorkin, Kairit Sirts,
Abstract summary: We present our submission to the AXOLOTL-24 shared task. The task comprises two subtasks: identifying new senses that words gain with time and producing the definitions for the identified new senses. We trained adapter-based binary classification models to match glosses with usage examples and leveraged the probability output of the models to identify novel senses.
Score: 0.21485350418225246
License: http://creativecommons.org/licenses/by/4.0/
Abstract: We present our submission to the AXOLOTL-24 shared task. The shared task comprises two subtasks: identifying new senses that words gain with time (when comparing newer and older time periods) and producing the definitions for the identified new senses. We implemented a conceptually simple and computationally inexpensive solution to both subtasks. We trained adapter-based binary classification models to match glosses with usage examples and leveraged the probability output of the models to identify novel senses. The same models were used to match examples of novel sense usages with Wiktionary definitions. Our submission attained third place on the first subtask and the first place on the second subtask.

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