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

Yuval Pinter; Cassandra L. Jacobs; Max Bittker

doi:10.18653/v1/2020.coling-main.572

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

Yuval Pinter, Cassandra L. Jacobs, Max Bittker

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings of the 28th International Conference on Computational Linguistics (Online)
Place of Publication	Barcelona
Publisher	International Committee on Computational Linguistics
Pages	6509-6515
Number of pages	7
DOIs	https://doi.org/10.18653/v1/2020.coling-main.572
State	Published - 1 Dec 2020

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@inproceedings{ac4cd261ed2a4d8c9abae4c40011e97d,

title = "NYTWIT: A Dataset of Novel Words in the New York Times",

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.",

author = "Yuval Pinter and Jacobs, {Cassandra L.} and Max Bittker",

year = "2020",

month = dec,

day = "1",

doi = "10.18653/v1/2020.coling-main.572",

language = "English",

pages = "6509--6515",

booktitle = "Proceedings of the 28th International Conference on Computational Linguistics (Online)",

publisher = "International Committee on Computational Linguistics",

}

NYTWIT: A Dataset of Novel Words in the New York Times. / Pinter, Yuval; Jacobs, Cassandra L.; Bittker, Max.
Proceedings of the 28th International Conference on Computational Linguistics (Online). Barcelona: International Committee on Computational Linguistics, 2020. p. 6509-6515.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Bittker, Max

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N2 - 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.

AB - 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.

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DO - 10.18653/v1/2020.coling-main.572

M3 - Conference contribution

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BT - Proceedings of the 28th International Conference on Computational Linguistics (Online)

PB - International Committee on Computational Linguistics

CY - Barcelona

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

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