NYTWIT: A Dataset of Novel Words in the New York Times

Yuval Pinter, Cassandra L. Jacobs, Max Bittker


Abstract
We present the New York Times Word Innovation Types dataset, or NYTWIT, a collection of over 2,500 novel English words published in the New York Times between November 2017 and March 2019, manually annotated for their class of novelty (such as lexical derivation, dialectal variation, blending, or compounding). We present baseline results for both uncontextual and contextual prediction of novelty class, showing that there is room for improvement even for state-of-the-art NLP systems. We hope this resource will prove useful for linguists and NLP practitioners by providing a real-world environment of novel word appearance.
Anthology ID:
2020.coling-main.572
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
6509–6515
Language:
URL:
https://aclanthology.org/2020.coling-main.572
DOI:
10.18653/v1/2020.coling-main.572
Bibkey:
Cite (ACL):
Yuval Pinter, Cassandra L. Jacobs, and Max Bittker. 2020. NYTWIT: A Dataset of Novel Words in the New York Times. In Proceedings of the 28th International Conference on Computational Linguistics, pages 6509–6515, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
NYTWIT: A Dataset of Novel Words in the New York Times (Pinter et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-main.572.pdf
Code
 yuvalpinter/nytwit
Data
NYTWIT