Shared task: Lexical semantic change detection in German (Student Project Report)
This work provides a benchmark for researchers in NLP to evaluate semantic change detection methods, but it is incremental as it applies an existing framework to a new language and task.
The paper tackled the lack of benchmarks for comparing semantic change detection systems by presenting results from the first shared task on unsupervised lexical semantic change detection in German, using an existing evaluation framework.
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).