English WordNet Random Walk Pseudo-Corpora

Filip Klubička, Alfredo Maldonado, Abhijit Mahalunkar, John Kelleher

Abstract
This is a resource description paper that describes the creation and properties of a set of pseudo-corpora generated artificially from a random walk over the English WordNet taxonomy. Our WordNet taxonomic random walk implementation allows the exploration of different random walk hyperparameters and the generation of a variety of different pseudo-corpora. We find that different combinations of parameters result in varying statistical properties of the generated pseudo-corpora. We have published a total of 81 pseudo-corpora that we have used in our previous research, but have not exhausted all possible combinations of hyperparameters, which is why we have also published a codebase that allows the generation of additional WordNet taxonomic pseudo-corpora as needed. Ultimately, such pseudo-corpora can be used to train taxonomic word embeddings, as a way of transferring taxonomic knowledge into a word embedding space.
Anthology ID:
2020.lrec-1.602
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4893–4902
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.602
DOI:
Bibkey:
Cite (ACL):
Filip Klubička, Alfredo Maldonado, Abhijit Mahalunkar, and John Kelleher. 2020. English WordNet Random Walk Pseudo-Corpora. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 4893–4902, Marseille, France. European Language Resources Association.
Cite (Informal):
English WordNet Random Walk Pseudo-Corpora (Klubička et al., LREC 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/2020.lrec-1.602.pdf
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