Multi-word expressions (MWE) are a heterogeneous class of strings of words that we continuously encounter in our everyday language experience. They are characterized mainly by their “fixed nature”, so that they are also defined as lexical chunks or lexical bundles. In the present article we review the literature focused on identifying the neural correlates of the processing of these expressions. We identify three critical processing components integral to the compositional analysis of MWE meaning. These components include compositional analysis leading up to recognition, non-compositional analysis subsequent to recognition, and the integration of the meaning of the chunk. Importantly, we claim that MWE processing provides a valuable source of unique evidence regarding predictive processing during language comprehension. For this goal, future research should focus on relatively understudied MWE categories, and it should take advantage of novel methodological approaches aimed at characterizing MWE comprehension during natural language processing.
Composing, not-composing, and integrating: The neuroscience of multi-word expressions
Paolo CanalWriting – Original Draft Preparation
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2024-01-01
Abstract
Multi-word expressions (MWE) are a heterogeneous class of strings of words that we continuously encounter in our everyday language experience. They are characterized mainly by their “fixed nature”, so that they are also defined as lexical chunks or lexical bundles. In the present article we review the literature focused on identifying the neural correlates of the processing of these expressions. We identify three critical processing components integral to the compositional analysis of MWE meaning. These components include compositional analysis leading up to recognition, non-compositional analysis subsequent to recognition, and the integration of the meaning of the chunk. Importantly, we claim that MWE processing provides a valuable source of unique evidence regarding predictive processing during language comprehension. For this goal, future research should focus on relatively understudied MWE categories, and it should take advantage of novel methodological approaches aimed at characterizing MWE comprehension during natural language processing.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.