Shared task: Lexical semantic change detection in German (Student Project Report)

TL;DR

This paper reports on the first shared task for unsupervised lexical semantic change detection in German, highlighting the need for benchmarks to evaluate different NLP systems' ability to detect semantic shifts over time.

Contribution

It introduces a new shared task framework for LSCD in German, providing a benchmark for future research in this area.

Findings

First shared task on German LSCD

Evaluation framework established for unsupervised detection

Results demonstrate varying system performances

Abstract

Recent NLP architectures have illustrated in various ways how semantic change can be captured across time and domains. However, in terms of evaluation there is a lack of benchmarks to compare the performance of these systems against each other. We present the results of the first shared task on unsupervised lexical semantic change detection (LSCD) in German based on the evaluation framework proposed by Schlechtweg et al. (2019).