论文标题
论点的神经现实结构结构
Neural reality of argument structure constructions
论文作者
论文摘要
在词汇主义语言理论中,认为参数结构可以从动词的含义中预测。结果,动词是子句含义的主要决定因素。相比之下,构造语法学家提出,论证结构是在与动词不同的构造(或形式含义对)中编码的。数十年的心理语言学研究产生了有利于建筑观点的大量经验证据。在这里,我们适应了一些心理语言学研究,以探测基于变压器的语言模型(LMS)中参数结构结构(ASC)的存在。首先,使用句子排序实验,我们发现共享相同构造的句子在嵌入空间中比共享同一动词的句子更接近。此外,LMS越来越喜欢通过构造使用更多的输入数据进行分组,从而反映了非本地语言学习者的行为。其次,在基于“ jabberwocky”启动实验的“ jabberwocky”实验中,我们发现LMS ASC具有含义,即使在语义上是非敏感的句子中也是如此。我们的工作为LMS中的ASC提供了第一个证据,并强调了设计基于心理学研究的新型探测方法的潜力。
In lexicalist linguistic theories, argument structure is assumed to be predictable from the meaning of verbs. As a result, the verb is the primary determinant of the meaning of a clause. In contrast, construction grammarians propose that argument structure is encoded in constructions (or form-meaning pairs) that are distinct from verbs. Decades of psycholinguistic research have produced substantial empirical evidence in favor of the construction view. Here we adapt several psycholinguistic studies to probe for the existence of argument structure constructions (ASCs) in Transformer-based language models (LMs). First, using a sentence sorting experiment, we find that sentences sharing the same construction are closer in embedding space than sentences sharing the same verb. Furthermore, LMs increasingly prefer grouping by construction with more input data, mirroring the behaviour of non-native language learners. Second, in a "Jabberwocky" priming-based experiment, we find that LMs associate ASCs with meaning, even in semantically nonsensical sentences. Our work offers the first evidence for ASCs in LMs and highlights the potential to devise novel probing methods grounded in psycholinguistic research.