Assessing the influence of attractor-verb distance on grammatical
  agreement in humans and language models
Christos-Nikolaos Zacharopoulos Théo Desbordes Mathias Sablé-Meyer
Subject-verb agreement in the presence of an attractor noun located between
the main noun and the verb elicits complex behavior: judgments of
grammaticality are modulated by the grammatical features of the attractor. For
example, in the sentence "The girl near the boys likes climbing", the attractor
(boys) disagrees in grammatical number with the verb (likes), creating a
locally implausible transition probability. Here, we parametrically modulate
the distance between the attractor and the verb while keeping the length of the
sentence equal. We evaluate the performance of both humans and two artificial
neural network models: both make more mistakes when the attractor is closer to
the verb, but neural networks get close to the chance level while humans are
mostly able to overcome the attractor interference. Additionally, we report a
linear effect of attractor distance on reaction times. We hypothesize that a
possible reason for the proximity effect is the calculation of transition
probabilities between adjacent words. Nevertheless, classical models of
attraction such as the cue-based model might suffice to explain this
phenomenon, thus paving the way for new research. Data and analyses available
at https://osf.io/d4g6k