Difference between revisions of "Natural Language Inference (NLI) Task"

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* ([[2018_NeuralNaturalLanguageInferenceM|Chen et al., 2018]]) ⇒ [[author::Qian Chen]], [[author::Xiaodan Zhu]], [[author::Zhen-Hua Ling]], [[author::Diana Inkpen]], and [[author::Si Wei]]. ([[year::2018]]). “[https://aclweb.org/anthology/P18-1224 Neural Natural Language Inference Models Enhanced with External Knowledge].” In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018). [http://dx.doi.org/10.18653/v1/p18-1224 doi:10.18653/v1/p18-1224]
 
* ([[2018_NeuralNaturalLanguageInferenceM|Chen et al., 2018]]) ⇒ [[author::Qian Chen]], [[author::Xiaodan Zhu]], [[author::Zhen-Hua Ling]], [[author::Diana Inkpen]], and [[author::Si Wei]]. ([[year::2018]]). “[https://aclweb.org/anthology/P18-1224 Neural Natural Language Inference Models Enhanced with External Knowledge].” In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018). [http://dx.doi.org/10.18653/v1/p18-1224 doi:10.18653/v1/p18-1224]
 
** QUOTE: [[Reasoning]] and [[inference]] are central to both [[human]] and [[artificial intelligence]]. [[Natural language inference (NLI)]], also known as [[recognizing textual entailment (RTE)]], is an important [[NLP]] problem concerned with determining [[inferential relationship]] (e.g., [[entailment]], [[contradiction]], or [[neutral]]) between a [[premise]] p and a [[hypothesis]] h. In general, [[modeling informal inference]] in [[language]] is a very challenging and basic problem towards achieving true [[natural language understanding]].
 
** QUOTE: [[Reasoning]] and [[inference]] are central to both [[human]] and [[artificial intelligence]]. [[Natural language inference (NLI)]], also known as [[recognizing textual entailment (RTE)]], is an important [[NLP]] problem concerned with determining [[inferential relationship]] (e.g., [[entailment]], [[contradiction]], or [[neutral]]) between a [[premise]] p and a [[hypothesis]] h. In general, [[modeling informal inference]] in [[language]] is a very challenging and basic problem towards achieving true [[natural language understanding]].
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=== 2017 ===
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* ([[2017_AnOverviewofNaturalLanguageInfe|Chatzikyriakidis et al., 2017]]) ⇒ [[author::Stergios Chatzikyriakidis]], [[author::Robin Cooper]], [[author::Simon Dobnik]], and [[author::Staffan Larsson]]. ([[year::2017]]). “[https://www.aclweb.org/anthology/W17-7203 An Overview of Natural Language Inference Data Collection: The Way Forward?].” In: [[Proceedings of the Computing Natural Language Inference Workshop]].
  
 
=== 2016a ===
 
=== 2016a ===

Revision as of 03:58, 13 September 2019

A Natural Language Inference (NLI) Task is an inference task of determining a inferential relationship between natural language hypothesis and premise.



References

2019

2018

2017

2016a

2016b

2009