A semantic universal, which we here dub the Veridical Uniformity Universal, has recently been argued to hold of responsive verbs (those that take both declarative and interrogative complements). This paper offers a preliminary explanation of this universal: verbs satisfying it are easier to learn than those that do not. This claim is supported by a computational experiment using artificial neural networks, mirroring a recent proposal for explaining semantic universals of quantifiers. This preliminary study opens up many avenues for future work on explaining semantic universals more generally, which are discussed in the conclusion.

中文翻译：

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普遍统一的解释

语义通用性，我们在这里称为“ Veridical Uniformity Universal”，最近被认为包含响应性动词（同时使用陈述性和疑问性补语的动词）。本文提供了对此通用性的初步解释：满足条件的动词比不满足要求的动词更容易学习。这项主张得到了使用人工神经网络的计算实验的支持，该实验与最近提出的解释量词语义通用性的提议相呼应。这项初步研究为将来更广泛地解释语义通用性的工作开辟了许多途径，并在结论中进行了讨论。