COLING 2020main13 citations
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.
BibTeX
@inproceedings{pinter-etal-2020-nytwit,
title = "{NYTWIT}: A Dataset of Novel Words in the {N}ew {Y}ork {T}imes",
author = "Pinter, Yuval and
Jacobs, Cassandra L. and
Bittker, Max",
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.572/",
doi = "10.18653/v1/2020.coling-main.572",
pages = "6509--6515"
}