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22 - Construction Grammar and Language Models

from Part VI - Constructional Applications

Published online by Cambridge University Press:  30 January 2025

By
Harish Tayyar Madabushi ,
Laurence Romain ,
Petar Milin  and
Dagmar Divjak
Edited by
Mirjam Fried  and
Kiki Nikiforidou
Mirjam Fried
Affiliation:
Univerzita Karlova
Kiki Nikiforidou
Affiliation:
University of Athens, Greece
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Summary

Recent progress in deep learning and natural language processing has given rise to powerful models that are primarily trained on a cloze-like task and show some evidence of having access to substantial linguistic information, including some constructional knowledge. This groundbreaking discovery presents an exciting opportunity for a synergistic relationship between computational methods and Construction Grammar research. In this chapter, we explore three distinct approaches to the interplay between computational methods and Construction Grammar: (i) computational methods for text analysis, (ii) computational Construction Grammar, and (iii) deep learning models, with a particular focus on language models. We touch upon the first two approaches as a contextual foundation for the use of computational methods before providing an accessible, yet comprehensive overview of deep learning models, which also addresses reservations construction grammarians may have. Additionally, we delve into experiments that explore the emergence of constructionally relevant information within these models while also examining the aspects of Construction Grammar that may pose challenges for these models. This chapter aims to foster collaboration between researchers in the fields of natural language processing and Construction Grammar. By doing so, we hope to pave the way for new insights and advancements in both these fields.

Keywords

deep learningnatural language processinglanguage modelsConstruction Grammar
Type
Chapter
Information
The Cambridge Handbook of Construction Grammar , pp. 572 - 595
Publisher: Cambridge University Press
Print publication year: 2025

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