What Kind of Natural Language Inference are NLP Systems Learning: Is this Enough?

Jean-Philippe Bernardy, Stergios Chatzikyriakidis

Abstract

In this paper, we look at Natural Language Inference, arguing that the notion of inference the current NLP systems are learning is much narrower compared to the range of inference patterns found in human reasoning. We take a look at the history and the nature of creating datasets for NLI. We discuss the datasets that are mainly used today for the relevant tasks and show why those are not enough to generalize to other reasoning tasks, e.g. logical and legal reasoning, or reasoning in dialogue settings. We then proceed to propose ways in which this can be remedied, effectively producing more realistic datasets for NLI. Lastly, we argue that the NLP community could have been too hasty to altogether dismiss symbolic approaches in the study of NLI, given that these might still be relevant for more fine-grained cases of reasoning. As such, we argue for a more pluralistic take on tackling NLI, favoring hybrid rather than non-hybrid approaches.

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Paper Citation


in Harvard Style

Bernardy J. and Chatzikyriakidis S. (2019). What Kind of Natural Language Inference are NLP Systems Learning: Is this Enough?.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: NLPinAI, ISBN 978-989-758-350-6, pages 919-931. DOI: 10.5220/0007683509190931


in Bibtex Style

@conference{nlpinai19,
author={Jean-Philippe Bernardy and Stergios Chatzikyriakidis},
title={What Kind of Natural Language Inference are NLP Systems Learning: Is this Enough?},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: NLPinAI,},
year={2019},
pages={919-931},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007683509190931},
isbn={978-989-758-350-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: NLPinAI,
TI - What Kind of Natural Language Inference are NLP Systems Learning: Is this Enough?
SN - 978-989-758-350-6
AU - Bernardy J.
AU - Chatzikyriakidis S.
PY - 2019
SP - 919
EP - 931
DO - 10.5220/0007683509190931