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arxiv: 1809.02922 · v2 · pith:KGZFKOWInew · submitted 2018-09-09 · 💻 cs.CL

Transforming Question Answering Datasets Into Natural Language Inference Datasets

Dorottya Demszky , Kelvin Guu , Percy Liang This is my paper
classification 💻 cs.CL
keywords datasetsinferencelanguageansweringautomaticallydatasetnaturalquestion
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Existing datasets for natural language inference (NLI) have propelled research on language understanding. We propose a new method for automatically deriving NLI datasets from the growing abundance of large-scale question answering datasets. Our approach hinges on learning a sentence transformation model which converts question-answer pairs into their declarative forms. Despite being primarily trained on a single QA dataset, we show that it can be successfully applied to a variety of other QA resources. Using this system, we automatically derive a new freely available dataset of over 500k NLI examples (QA-NLI), and show that it exhibits a wide range of inference phenomena rarely seen in previous NLI datasets.

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Cited by 5 Pith papers

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