@inproceedings{schwab2022sinatra,
  abstract = {We present a cross-lingual approach for the extraction of Vossian Antonomasia, a stylistic device especially popular in newspaper articles. We evaluate a zero-shot transfer learning approach and two approaches that use machine-translated training and test data. We show that our proposed models achieve strong results on all test datasets in the target language. As annotated data is sparse, especially in the target language, we generate additional test data to evaluate our models and conclude with a robustness study on real-world data.},
  added-at = {2022-11-16T08:48:29.000+0100},
  author = {Schwab, Michel and Jäschke, Robert and Fischer, Frank},
  biburl = {https://www.bibsonomy.org/bibtex/2e68d487a554f79407c532889e826b3d8/jaeschke},
  booktitle = {Proceedings of the 5th International Conference on Natural Language and Speech Processing},
  interhash = {1bc2a3b9d2e31e9baa3879548253a255},
  intrahash = {e68d487a554f79407c532889e826b3d8},
  keywords = {2022 cross-lingual extraction fewshot myown nlp vossanto},
  pages = {282--287},
  publisher = {Association for Computational Linguistics},
  series = {ICNLSP'22},
  timestamp = {2024-03-13T13:00:03.000+0100},
  title = {»Der Frank Sinatra der Wettervorhersage« – Cross-Lingual Vossian Antonomasia Extraction},
  url = {https://aclanthology.org/2022.icnlsp-1.33/},
  year = 2022
}