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A Domain-Specific Dataset of Difficulty Ratings for German Noun Compounds in the Domains DIY, Cooking and Automotive.

, , , and . LREC, page 4359-4367. European Language Resources Association, (2020)

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CL-IMS @ DIACR-Ita: Volente o Nolente: BERT does not outperform SGNS on Semantic Change Detection., , , , and . CoRR, (2020)Simulating Lexical Semantic Change from Sense-Annotated Data., and . CoRR, (2020)The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change., , , , , , , , and . CoRR, (2023)The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change., , , , , , , , and . EACL (Demonstrations), page 137-149. Association for Computational Linguistics, (2024)Made of Steel? Learning Plausible Materials for Components in the Vehicle Repair Domain., , and . EACL, page 1412-1427. Association for Computational Linguistics, (2023)What Drives the Use of Metaphorical Language? Negative Insights from Abstractness, Affect, Discourse Coherence and Contextualized Word Representations., and . *SEM@NAACL-HLT, page 299-310. Association for Computational Linguistics, (2022)IMS at SemEval-2020 Task 1: How Low Can You Go? Dimensionality in Lexical Semantic Change Detection., , , and . SemEval@COLING, page 81-89. International Committee for Computational Linguistics, (2020)To Split or Not to Split: Composing Compounds in Contextual Vector Spaces., , and . EMNLP, page 16131-16136. Association for Computational Linguistics, (2023)AkkuBohrHammer vs. AkkuBohrhammer: Experiments towards the Evaluation of Compound Splitting Tools for General Language and Specific Domains., , , , , and . KONVENS, (2019)Distinguishing between paradigmatic semantic relations across word classes: human ratings and distributional similarity.. J. Lang. Model., 8 (1): 53-101 (2020)