MED (Monotonicity Entailment Dataset)

Introduced by Yanaka et al. in Can neural networks understand monotonicity reasoning?

MED is a new evaluation dataset that covers a wide range of monotonicity reasoning that was created by crowdsourcing and collected from linguistics publications. The dataset was constructed by collecting naturally-occurring examples by crowdsourcing and well-designed ones from linguistics publications. It consists of 5,382 examples.

Source: https://github.com/verypluming/MED

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