is learned by humans as a general abstract feature of language [see @scheepers2003syntactic]. In other words, human syntactic representations of attachment overlap, with prepositional attachment influencing relative clause attachment, etc. These relationships could coalesce during training and result in an attachment preference that differs from any one structure individually. However, it is clear that whatever attachment biases exist in the data are insufficient for RNNs to learn a human-like attachment preference in Spanish. This provides compelling evidence that standard training data itself may systematically lack aspects of syntax relevant to performing linguistic comprehension tasks.

We suspect that there are deep systematic issues leading to this mismatch between the expected distribution of human attachment preferences and the actual distribution of attachment in the Spanish training corpus. Experimental findings from psycholinguistics suggest that this issue could follow from a more general mismatch between language production and language comprehension. In particular, @kehleretal2015 [@kehleretal2018] have provided empirical evidence that the production and comprehension of these structures are guided by different biases in humans. Production is guided by syntactic and information structural considerations (e.g., topic), while comprehension is influenced by those considerations plus pragmatic and discourse factors (e.g., coherence relations). As such, the biases in 