WiC-TSV-de: German Word-in-Context Target-Sense-Verification Dataset and Cross-Lingual Transfer Analysis
Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)
Abstract
Target Sense Verification (TSV) describes the binary disambiguation task of deciding whether the intended sense of a target word in a context corresponds to a given target sense. In this paper, we introduce WiC-TSV-de, a multi-domain dataset for German Target Sense Verification. While the training and development sets consist of domain-independent instances only, the test set contains domain-bound subsets, originating from four different domains, being Gastronomy, Medicine, Hunting, and Zoology. The domain-bound subsets incorporate adversarial examples such as in-domain ambiguous target senses and context-mixing (i.e., using the target sense in an out-of-domain context) which contribute to the challenging nature of the presented dataset. WiC-TSV-de allows for the development of sense-inventory-independent disambiguation models that can generalise their knowledge for different domain settings. By combining it with the original English WiC-TSV benchmark, we performed monolingual and cross-lingual analysis, where the evaluated baseline models were not able to solve the dataset to a satisfying degree, leaving a big gap to human performance.