Natural Language Inference

Natural language inference (NLI) is the task of determining whether a "hypothesis" is true (entailment), false (contradiction), or undetermined (neutral) given a "premise". Example: Premise Label Hypothesis A man inspects the uniform of a figure in some East Asian country. contradiction The man is sleeping. An older and younger man smiling. neutral Two men are smiling and laughing at the cats playing on the floor. A soccer game with multiple males playing. entailment Some men are playing a sport. Approaches used for NLI include earlier symbolic and statistical approaches to more recent deep learning approaches. Benchmark datasets used for NLI include SNLI, MultiNLI, SciTail, among others. You can get hands-on practice on the SNLI task by following this d2l.ai chapter. Further readings: Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches