Semantically Informed Slang Interpretation

Anonymous

Paper Link: https://openreview.net/forum?id=_q_aybC1ZS3

Paper Type: Long paper (up to eight pages of content + unlimited references and appendices)

Abstract: Slang is a predominant form of informal language making flexible and extended use of words that is notoriously hard for natural language processing systems to interpret. Existing approaches to slang interpretation tend to rely on context but ignore semantic extensions common in slang word usage. We propose a semantically informed slang interpretation (SSI) framework that considers jointly the contextual and semantic appropriateness of a candidate interpretation for a query slang. We perform rigorous evaluation on two large-scale online slang dictionaries and show that our approach not only achieves state-of-the-art accuracy for slang interpretation in English, but also does so in zero-shot and few-shot scenarios where training data is sparse. Furthermore, we show how the same framework can be applied to enhancing machine translation of slang from English to other languages. Our work creates opportunities for the automated interpretation and translation of informal language.

Presentation Mode: This paper will be presented virtually

Virtual Presentation Timezone: UTC-5

Copyright Consent Signature (type Name Or NA If Not Transferrable): Zhewei Sun

Copyright Consent Name And Address: University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1