@inproceedings{ni-wang-2017-learning,
title = "Learning to Explain Non-Standard {E}nglish Words and Phrases",
author = "Ni, Ke and
Wang, William Yang",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-2070",
pages = "413--417",
abstract = "We describe a data-driven approach for automatically explaining new, non-standard English expressions in a given sentence, building on a large dataset that includes 15 years of crowdsourced examples from UrbanDictionary.com. Unlike prior studies that focus on matching keywords from a slang dictionary, we investigate the possibility of learning a neural sequence-to-sequence model that generates explanations of unseen non-standard English expressions given context. We propose a dual encoder approach{---}a word-level encoder learns the representation of context, and a second character-level encoder to learn the hidden representation of the target non-standard expression. Our model can produce reasonable definitions of new non-standard English expressions given their context with certain confidence.",
}
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%0 Conference Proceedings
%T Learning to Explain Non-Standard English Words and Phrases
%A Ni, Ke
%A Wang, William Yang
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F ni-wang-2017-learning
%X We describe a data-driven approach for automatically explaining new, non-standard English expressions in a given sentence, building on a large dataset that includes 15 years of crowdsourced examples from UrbanDictionary.com. Unlike prior studies that focus on matching keywords from a slang dictionary, we investigate the possibility of learning a neural sequence-to-sequence model that generates explanations of unseen non-standard English expressions given context. We propose a dual encoder approach—a word-level encoder learns the representation of context, and a second character-level encoder to learn the hidden representation of the target non-standard expression. Our model can produce reasonable definitions of new non-standard English expressions given their context with certain confidence.
%U https://aclanthology.org/I17-2070
%P 413-417
Markdown (Informal)
[Learning to Explain Non-Standard English Words and Phrases](https://aclanthology.org/I17-2070) (Ni & Wang, IJCNLP 2017)
ACL
- Ke Ni and William Yang Wang. 2017. Learning to Explain Non-Standard English Words and Phrases. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 413–417, Taipei, Taiwan. Asian Federation of Natural Language Processing.