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21 - Construction Grammar and Artificial Intelligence

from Part VI - Constructional Applications

Published online by Cambridge University Press:  30 January 2025

By
Katrien Beuls  and
Paul Van Eecke
Edited by
Mirjam Fried  and
Kiki Nikiforidou
Mirjam Fried
Affiliation:
Univerzita Karlova
Kiki Nikiforidou
Affiliation:
University of Athens, Greece
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Summary

In this chapter, we argue that it is highly beneficial for the contemporary construction grammarian to have a thorough understanding of the strong relationship between the research fields of Construction Grammar and artificial intelligence. We start by unraveling the historical links between the two fields, showing that their relationship is rooted in a common attitude towards human communication and language. We then discuss the first direction of influence, focusing on how insights and techniques from the field of artificial intelligence play an important role in operationalizing, validating, and scaling constructionist approaches to language. We then proceed to the second direction of influence, highlighting the relevance of Construction Grammar insights and analyses to the artificial intelligence endeavor of building truly intelligent agents. We support our case with a variety of illustrative examples and conclude that further elaboration of this relationship will play a key role in shaping the future of the field of Construction Grammar.

Keywords

computational Construction Grammarartificial intelligenceConstruction Grammar applicationslearning Construction GrammarsFluid Construction Grammar
Type
Chapter
Information
The Cambridge Handbook of Construction Grammar , pp. 543 - 571
Publisher: Cambridge University Press
Print publication year: 2025

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References

Abend, O., Kwiatkowski, T., Smith, N. J., Goldwater, S., & Steedman, M. (2017). Bootstrapping language acquisition. Cognition, 164, 116–143.CrossRefGoogle ScholarPubMed
Baker, C. F., Fillmore, C. J., & Lowe, J. B. (1998). The Berkeley FrameNet project. In Proceedings of the 17th International Conference on Computational Linguistics, Vol. 1. Washington, DC: Association for Computational Linguistics, pp. 86–90.Google Scholar
Banarescu, L., Bonial, C., Cai, S., Georgescu, M., Griffitt, K., Hermjakob, U., Knight, K., Koehn, P., Palmer, M., & Schneider, N. (2013). Abstract Meaning Representation for Sembanking. In Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse. Washington, DC: Association for Computational Linguistics, pp. 178–186.Google Scholar
Baronchelli, A., Felici, M., Loreto, V., Caglioti, E., & Steels, L. (2006). Sharp transition towards shared vocabularies in multi-agent systems. Journal of Statistical Mechanics: Theory and Experiment, 2006(6), P06014. https://doi.org/10.1088/1742-5468/2006/06/P06014.CrossRefGoogle Scholar
Bergen, B. & Chang, N. (2005). Embodied Construction Grammar in simulation-based language understanding. In Östman, J.-O. & Fried, M., eds., Construction Grammars: Cognitive Grounding and Theoretical Extensions. Amsterdam & Philadelphia: John Benjamins, pp. 147–190.CrossRefGoogle Scholar
Beuls, K., Gerasymova, K., & van Trijp, R. (2010). Situated learning through the use of language games. In Proceedings of the 19th Annual Machine Learning Conference of Belgium and The Netherlands (BeNeLearn), pp. 1–6.Google Scholar
Beuls, K. & Steels, L. (2013). Agent-based models of strategies for the emergence and evolution of grammatical agreement. PLoS ONE, 8(3), e58960. https://doi.org/10.1371/journal.pone.0058960.CrossRefGoogle ScholarPubMed
Beuls, K. & Van Eecke, P. (2023). Fluid Construction Grammar: State of the art and future outlook. In Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023). Washington, DC: Association for Computational Linguistics, pp. 41–50.Google Scholar
Beuls, K., Van Eecke, P., & Cangalovic, V. S. (2021). A computational construction grammar approach to semantic frame extraction. Linguistics Vanguard, 7(1), 20180015. https://doi.org/10.1515/lingvan-2018-0015.CrossRefGoogle Scholar
Bleys, J., Stadler, K., & De Beule, J. (2011). Search in linguistic processing. In Steels, L., ed., Design Patterns in Fluid Construction Grammar. Amsterdam & Philadelphia: John Benjamins, pp. 149–179.CrossRefGoogle Scholar
Bleys, J. & Steels, L. (2009). Linguistic selection of language strategies: A case study for color. In Proceedings of the 10th European Conference on Artificial Life, pp. 150–157.Google Scholar
Bonial, C., Badarau, B., Griffitt, K., Hermjakob, U., Knight, K., O’Gorman, T., Palmer, M., & Schneider, N. (2018). Abstract Meaning Representation of constructions: The more we include, the better the representation. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). Miyazaki: European Language Resources Association (ELRA), pp. 1677–1684.Google Scholar
Chang, N. (2008). Constructing Grammar: A Computational Model of the Emergence of Early Constructions. PhD thesis. University of California, Berkeley.Google Scholar
Croft, W. (2001). Radical Construction Grammar: Syntactic Theory in Typological Perspective. Oxford: Oxford University Press.CrossRefGoogle Scholar
de Boer, B. (2000). Self-organization in vowel systems. Journal of Phonetics, 28(4), 441–465.CrossRefGoogle Scholar
de Vylder, B. & Tuyls, K. (2006). How to reach linguistic consensus: A proof of convergence for the naming game. Journal of Theoretical Biology, 242(4), 818–831.CrossRefGoogle Scholar
Dominey, P. F. & Boucher, J.-D. (2005). Learning to talk about events from narrated video in a construction grammar framework. Artificial Intelligence, 167(1), 31–61.CrossRefGoogle Scholar
Doumen, J., Beuls, K., & Van Eecke, P. (2023). Modelling language acquisition through syntactico-semantic pattern finding. In Findings of the Association for Computational Linguistics, EACL 2023, pp. 1347–1357.CrossRefGoogle Scholar
Feldman, J., Dodge, E., & Bryant, J. (2009). Embodied Construction Grammar. In Heine, B. & Narrog, H., eds., The Oxford Handbook of Linguistic Analysis. Oxford: Oxford University Press, pp. 121–146.Google Scholar
Fillmore, C. J. (1968). The case for case. In Bach, E. W. & Harms, R. T., eds., Universals in Linguistic Theory. New York: Holt, Rinehart and Winston, pp. 1–88.Google Scholar
Fillmore, C. J. (1976). Frame semantics and the nature of language. Annals of the New York Academy of Sciences: Conference on the Origin and Development of Language and Speech, 280(1), 20–32.CrossRefGoogle Scholar
Fillmore, C. J. (1988). The mechanisms of “Construction Grammar”. Annual Meeting of the Berkeley Linguistics Society 14, 35–55.CrossRefGoogle Scholar
Fillmore, C. J. & Baker, C. F. (2001). Frame semantics for text understanding. In Proceedings of WordNet and Other Lexical Resources Workshop, NAACL, 6.Google Scholar
Fillmore, C. J., Kay, P., & O’Connor, M. C. (1988). Regularity and idiomaticity in grammatical constructions: The case of let alone. Language, 64(3), 501–538.CrossRefGoogle Scholar
Fried, M. & Östman, J.-O. (2004). Construction Grammar: A thumbnail sketch. In Fried, M. & Östman, J.-O., eds., Construction Grammar in a Cross-Language Perspective. Amsterdam & Philadelphia: John Benjamins, pp. 1–86.CrossRefGoogle Scholar
Gaspers, J., Cimiano, P., Griffiths, S. S., & Wrede, B. (2011). An unsupervised algorithm for the induction of constructions. 2011 IEEE International Conference on Development and Learning (ICDL), 2, 1–6.Google Scholar
Gerasymova, K. & Spranger, M. (2010). Acquisition of grammar in autonomous artificial systems. In Coelho, M., Studer, R. & Wooldridge, M., eds., Proceedings of the 19th European Conference on Artificial Intelligence (ECAI-2010). Amsterdam: IOS Press, pp. 923–928.Google Scholar
Goffman, E. (1974). Frame Analysis: An Essay on the Organization of Experience. Cambridge, MA: Harvard University Press.Google Scholar
Goldberg, A. E. (1995). Constructions: A Construction Grammar Approach to Argument Structure. Chicago: University of Chicago Press.Google Scholar
Goldberg, A. E. (2006). Constructions at Work: The Nature of Generalization in Language. Oxford: Oxford University Press.Google Scholar
Hilpert, M. (2014). Construction Grammar and Its Application to English. Edinburgh: Edinburgh University Press.Google Scholar
Hilpert, M. (2021). Ten Lectures on Diachronic Construction Grammar. Leiden: Brill.CrossRefGoogle Scholar
Jurafsky, D. (2014). Charles J. Fillmore. Computational Linguistics, 40(3), 725–731.CrossRefGoogle Scholar
Kay, P. & Fillmore, C. J. (1999). Grammatical constructions and linguistic generalizations: The What’s x Doing Y? construction. Language, 75(1), 1–33.CrossRefGoogle Scholar
Michaelis, L. A. (2013). Sign-Based Construction Grammar. In Hoffmann, T. & Trousdale, G., eds., The Oxford Handbook of Construction Grammar. Oxford: Oxford University Press, pp. 133–152.Google Scholar
Mikolov, T., Joulin, A., & Baroni, M. (2016). A roadmap towards machine intelligence. In Proceedings of the International Conference on Intelligent Text Processing and Computational Linguistics, pp. 29–61.Google Scholar
Minsky, M. (1974). A Framework for Representing Knowledge. Cambridge, MA: MIT AI Laboratory.Google Scholar
Nevens, J., Doumen, J., Van Eecke, P., & Beuls, K. (2022). Language acquisition through intention reading and pattern finding. In Proceedings of the 29th International Conference on Computational Linguistics, pp. 15–25.Google Scholar
Nevens, J., Van Eecke, P., & Beuls, K. (2020). From continuous observations to symbolic concepts: A discrimination-based strategy for grounded concept learning. Frontiers in Robotics and AI, 7, 84.CrossRefGoogle Scholar
Newell, A. & Simon, H. (1956). The logic theory machine – a complex information processing system. IRE Transactions on Information Theory, 2(3), 61–79.CrossRefGoogle Scholar
Oudeyer, P.-Y. (2006). Self-organization in the Evolution of Speech. Oxford: Oxford University Press.CrossRefGoogle Scholar
Pearl, J. (1984). Heuristics: Intelligent Search Strategies for Computer Problem Solving. Boston: Addison-Wesley Longman Publishing.Google Scholar
Rumelhart, D. E. (1980). Schemata: The building blocks of cognition. In Spiro, R., Bruce, B., & Brewer, W., eds., Theoretical Issues in Reading Comprehension. Hillsdale: Lawrence Erlbaum Associates, pp. 33–58.Google Scholar
Russell, S. & Norvig, P. (2021). Artificial Intelligence: A Modern Approach, 4th edition. Hoboken: Pearson.Google Scholar
Sag, I. A. (2012). Sign-Based Construction Grammar: An informal synopsis. In Boas, H. C. & Sag, I. A., eds., Sign-Based Construction Grammar. Stanford: CSLI Publications, pp. 69–202.Google Scholar
Schank, R. C. & Abelson, R. P. (1977). Scripts, Plans, Goals, and Understanding: An Inquiry into Human Knowledge Structures. Hillsdale: Lawrence Erlbaum Associates.Google Scholar
Sierra Santibáñez, J. (2012). A logic programming approach to parsing and production in Fluid Construction Grammar. In Steels, L., ed., Computational Issues in Fluid Construction Grammar. Berlin: Springer, pp. 239–255.CrossRefGoogle Scholar
Spranger, M. (2016). The Evolution of Grounded Spatial Language. Berlin: Language Science Press.CrossRefGoogle Scholar
Spranger, M. & Steels, L. (2015). Co-acquisition of syntax and semantics: An investigation in spatial language. In Yang, Q. & Wooldridge, M., eds., Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Palo Alto: AAAI Press, pp. 1909–1915.Google Scholar
Steels, L. (1998). The origins of syntax in visually grounded robotic agents. Artificial Intelligence, 103(1-2), 133–156.CrossRefGoogle Scholar
Steels, L. (2001). Language games for autonomous robots. IEEE Intelligent Systems, 16(5), 16–22.CrossRefGoogle Scholar
Steels, L. (2004). Constructivist development of grounded Construction Grammar. In Daelemans, W. & Walker, M., eds., Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics. Barcelona: Association for Computational Linguistic Conference, pp. 9–19. https://doi.org/10.3115/1218955.1218957.Google Scholar
Steels, L. (2005). The emergence and evolution of linguistic structure: From lexical to grammatical communication systems. Connection Science, 17, 213–230.CrossRefGoogle Scholar
Steels, L. (2015). The Talking Heads Experiment: Origins of Words and Meanings. Berlin: Language Science Press.CrossRefGoogle Scholar
Steels, L. & Belpaeme, T. (2005). Coordinating perceptually grounded categories through language: A case study for colour. Behavioral and Brain Sciences, 28(4), 469–488.CrossRefGoogle Scholar
Steels, L. & De Beule, J. (2006). Unify and merge in Fluid Construction Grammar. In Vogt, P., Sugita, Y., Tuci, E., & Nehaniv, C., eds., Symbol Grounding and Beyond. Berlin & Heidelberg: Springer, pp. 197–223.CrossRefGoogle Scholar
Steels, L., Van Eecke, P., & Beuls, K. (2022). Usage-based learning of grammatical categories. arXiv:2204.10201. https://doi.org/10.48550/arXiv.2204.10201.CrossRefGoogle Scholar
Sunstein, C. R. (2018). #Republic. Princeton: Princeton University Press.Google Scholar
Tomasello, M. (2003). Constructing a Language: A Usage-Based Theory of Language Acquisition. Cambridge, MA: Harvard University Press.Google Scholar
Tomasello, M. (2009). The usage-based theory of language acquisition. In Bavin, E. L., ed., The Cambridge Handbook of Child Language. Cambridge: Cambridge University Press, pp. 69–87.CrossRefGoogle Scholar
Van Eecke, P. (2018). Generalisation and Specialisation Operators for Computational Construction Grammar and Their Application in Evolutionary Linguistics Research. PhD thesis. Vrije Universiteit Brussel.Google Scholar
Van Eecke, P. & Beuls, K. (2017). Meta-layer problem solving for computational Construction Grammar. In The 2017 AAAI Spring Symposium Series. Palo Alto: AAAI Press, pp. 258–265.Google Scholar
Van Eecke, P. & Beuls, K. (2018). Exploring the creative potential of computational Construction Grammar. Zeitschrift für Anglistik und Amerikanistik, 66(3), 341–355.CrossRefGoogle Scholar
Van Eecke, P., Nevens, J., & Beuls, K. (2022). Neural heuristics for scaling constructional language processing. Journal of Language Modelling, 10(2), 287–314.CrossRefGoogle Scholar
van Trijp, R. (2008). The emergence of semantic roles in Fluid Construction Grammar. In Smith, A. D. M., Smith, K., & Ferrer i Cancho, R., eds., The Evolution Of Language: Proceedings of the 7th International Conference (EVOLANG7). Singapore: World Scientific, pp. 346–353.CrossRefGoogle Scholar
van Trijp, R. (2016). Chopping down the syntax tree: What constructions can do instead. Belgian Journal of Linguistics, 30(1), 15–38.CrossRefGoogle Scholar
van Trijp, R. & Steels, L. (2012). Multilevel alignment maintains language systematicity. Advances in Complex Systems, 15(3–4). https://doi.org/10.1142/S0219525912500397.CrossRefGoogle Scholar
van Trijp, R., Beuls, K., & Van Eecke, P. (2022). The FCG editor: An innovative environment for engineering computational construction grammars. PLoS ONE, 17(6). https://doi.org/10.1371/journal.pone.0269708.CrossRefGoogle ScholarPubMed
Wellens, P. & De Beule, J. (2010). Priming through constructional dependencies: a case study in Fluid Construction Grammar. In Smith, A. D. M., Schouwstra, M., de Boer, B., & Smith, K., eds., The Evolution of Language: Proceedings of the 8th International Conference (EVOLANG8). Singapore: World Scientific, pp. 344–351.CrossRefGoogle Scholar
Willaert, T., Van Eecke, P., Beuls, K., & Steels, L. (2020). Building social media observatories for monitoring online opinion dynamics. Social Media + Society, 6(2). https://doi.org/10.1177/205630511989.CrossRefGoogle Scholar
Willaert, T., Van Eecke, P., Van Soest, J., & Beuls, K. (2021). An opinion facilitator for online news media. Frontiers in Big Data, 4, https://doi.org/10.3389/fdata.2021.695667.CrossRefGoogle ScholarPubMed
Winston, P. H. (1977). Artificial Intelligence. Reading: Addison-Wesley.Google Scholar

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