Subject Verb Agreement Error Patterns in Meaningless Sentences: Humans vs. BERT

September 21, 2022 ยท Declared Dead ยท ๐Ÿ› International Conference on Computational Linguistics

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Authors Karim Lasri, Olga Seminck, Alessandro Lenci, Thierry Poibeau arXiv ID 2209.10538 Category cs.CL: Computation & Language Citations 6 Venue International Conference on Computational Linguistics Last Checked 4 months ago
Abstract
Both humans and neural language models are able to perform subject-verb number agreement (SVA). In principle, semantics shouldn't interfere with this task, which only requires syntactic knowledge. In this work we test whether meaning interferes with this type of agreement in English in syntactic structures of various complexities. To do so, we generate both semantically well-formed and nonsensical items. We compare the performance of BERT-base to that of humans, obtained with a psycholinguistic online crowdsourcing experiment. We find that BERT and humans are both sensitive to our semantic manipulation: They fail more often when presented with nonsensical items, especially when their syntactic structure features an attractor (a noun phrase between the subject and the verb that has not the same number as the subject). We also find that the effect of meaningfulness on SVA errors is stronger for BERT than for humans, showing higher lexical sensitivity of the former on this task.
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