@inproceedings{hole19:_distr_analy_funct_words,
  abstract = {In this paper, we are concerned with the phenomenon of function word polysemy. We adopt the framework of distributional semantics, which characterizes word meaning by observing occurrence contexts in large corpora and which is in principle well situated to model polysemy. Nevertheless, function words were traditionally considered as impossible to analyze distributionally due to their highly flexible usage patterns.

We establish that contextualized word embeddings, the most recent generation of distributional methods, offer hope in this regard. Using the German reflexive pronoun 'sich' as an example, we find that contextualized word embeddings capture theoretically motivated word senses for 'sich' to the extent to which these senses are mirrored systematically in linguistic usage.},
  added-at = {2019-06-04T09:28:34.000+0200},
  author = {Padó, Sebastian and Hole, Daniel},
  biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2385f2d2b83ced594888072db546bbd31/sp},
  booktitle = {Proceedings of the 13th International Tbilisi Symposium on Language, Logic and Computation 2019},
  interhash = {2037390fcf19e0af578910bcf7d27a0e},
  intrahash = {385f2d2b83ced594888072db546bbd31},
  keywords = {conference myown},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  timestamp = {2022-05-18T07:32:01.000+0200},
  title = {Distributional Analysis of Polysemous Function Words},
  url = {https://doi.org/10.1007/978-3-030-98479-3_6},
  volume = 13206,
  year = 2022
}