Cover not available
Article published In:
Lingvisticæ Investigationes
Vol. 45:1 (2022) ► pp.83–115

Evaluating morphosemantic demotivation through experimental and distributional methods

| Université de Fribourg
| Université Sorbonne Nouvelle
| Université Toulouse Jean Jaurès
| Université Toulouse Jean Jaurès
| Université Toulouse Jean Jaurès
| Université de Fribourg
The lexicalization of morphologically complex words, i.e. their inclusion in the lexicon, can involve a loss of semantic compositionality. Such a phenomenon, called demotivation, has been overlooked in both morphological and lexical studies, notably regarding its gradual nature. This paper compares two measures of demotivation based on experimental and distributional semantics approaches. It builds on the evaluation of 78 pairs of French verbs and derived nouns selected to represent three levels of demotivation. The comparison of the two approaches using speakers’ judgements and word vector similarity indicates convergence on the identification of demotivation degrees within a continuum, while also highlighting specific aspects of each method. The study provides direction to further research on morphosemantic demotivation, bridging together semantic, morphological and methodological considerations.
Keywords: demotivation, semantics, experimental approach, distributional semantics, lexicon
Article outline
  • Introduction
  • 1.Material selection
    • 1.1Characteristics of the verb-noun pairs
    • 1.2Data collection
  • 2.Experimental approach
    • 2.1Method
      • 2.1.1Participants
      • 2.1.2Procedure
    • 2.2Results
  • 3.Automatic measurement of demotivation
    • 3.1Design
    • 3.2Results
  • 4.Discussion
    • 4.1Convergence of experimental and distributional scores
    • 4.2Discrepancies between the two methods
    • 4.3Going further into the diachronic dimension of demotivation
  • 5.Conclusion
  • Acknowledgements
  • Notes
  • References
Published online: 5 December 2022
DOI logo
https://doi.org/10.1075/li.00068.wau
References (54)
References
Baayen, H. 1993. On frequency, transparency and productivity. In Yearbook of morphology 1992, p. 181–208. Springer. DOI logoGoogle Scholar
Baayen, R. H., Milin, P. & Ramscar, M. 2016. Frequency in lexical processing. Aphasiology, 30 (11), 1174–1220. DOI logoGoogle Scholar
Barca, L., Benedetti, F. & Pezzulo, G. 2016. The effects of phonological similarity on the semantic categorisation of pictorial and lexical stimuli: evidence from continuous behavioural measures. Journal of Cognitive Psychology, 28(2), 159–170. DOI logoGoogle Scholar
Bauer, L. 1983. English word-formation. Cambridge University Press. DOI logoGoogle Scholar
Benjamini, Y. & Hochberg, Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B, 57 (1), 289–300. DOI logoGoogle Scholar
Blank, A. 2001. Pathways of lexicalization. In M. Haspelmath, E. König, W. Oesterreicher & W. Raible, Eds., Language Typology and Language Universals, 1596–1608. De Gruyter Mouton.Google Scholar
Boleda, G. 2020. Distributional semantics and linguistic theory. Annual Review of Linguistics, 61, 213–234. DOI logoGoogle Scholar
Bonami, O. & Paperno, D. 2018. Inflection vs. derivation in a distributional vector space. Lingue e Linguaggio, 17(2), 173–195.Google Scholar
Bonami, O. & Thuilier, J. 2019. A statistical approach to rivalry in lexeme formation: French-iser and-ifier. Word structure, 12(1), 4–41. DOI logoGoogle Scholar
Bonami, O. & Tribout, D. 2021. Échantinom: a hand-annotated morphological lexicon of French nouns. In Proceedings of the Third International Workshop on Resources and Tools for Derivational Morphology (DeriMo 2021), 33–42, ATILF & CLLE, Université de Lorraine, Nancy, France.Google Scholar
Brinton, L. J. & Traugott, E. C. 2005. Lexicalization and language change. Cambridge University Press. DOI logoGoogle Scholar
Bullinaria, J. A. & Levy, J. P. 2007. Extracting semantic representations from word co-occurrence statistics: A computational study. Behavior research methods, 39(3), 510–526. DOI logoGoogle Scholar
Christensen, R. H. B. 2019. ordinal — regression models for ordinal data. R package version 2019.12-10. [URL]
Corbin, D. 1987. Morphologie dérivationnelle et structuration du lexique. Mouton De Gruyter.Google Scholar
Creemers, A., Goodwin Davies, A., Wilder, R. J., Tamminga, M. & Embick, D. 2020. Opacity, transparency, and morphological priming: A study of prefixed verbs in dutch. Journal of Memory and Language, 1101. DOI logoGoogle Scholar
Daneman, M. & Reingold, E. M. 2000. Chapter 17 - Do Readers Use Phonological Codes to Activate Word Meanings? Evidence from Eye Movements. In A. Kennedy, R. Radach, D. Heller & J. Pynte, Eds., Reading as a perceptual process, 447–474: Elsevier. DOI logoGoogle Scholar
Dendien, J. & Pierrel, J.-M. 2003. Le trésor de la langue française informatisé: un exemple d’ informatisation d’un dictionnaire de langue de référence. Traitement automatique des langues, 44(2), 11–37.Google Scholar
Dohmes, P., Zwitserlood, P. & Bölte, J. 2004. The impact of semantic transparency of morphologically complex words on picture naming. Brain and Language, 901, 203–212. DOI logoGoogle Scholar
Firth, J. R. 1957. A synopsis of linguistic theory, 1930–1955. In J. R. Firth, Ed., Studies in Linguistic Analysis, 1–32. Oxford: Basil Blackwell.Google Scholar
Gagné, C. L., Spalding, T. L. & Nisbet, K. A. 2017. Processing English compounds: Investigating semantic transparency. SKASE Journal of Theoretical Linguistics, 13 (2), 2–22.Google Scholar
Harris, Z. S. 1954. Distributional structure. Word, 10 (2–3), 146–162. DOI logoGoogle Scholar
Hathout, N., Sajous, F. & Calderone, B. 2014. GLÀFF, a Large Versatile French Lexicon. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14), Reykjavik, Iceland.Google Scholar
Hilpert, M. 2019. Lexicalization in morphology, In Oxford Research Encyclopedia of Linguistics, 1–18. Oxford University Press. DOI logoGoogle Scholar
Hohenhaus, P. 2005. Lexicalization and institutionalization. In Handbook of word-formation, 353–373. Springer. DOI logoGoogle Scholar
Hollander, M. & Wolfe, D. A. 1973. Nonparametric Statistical Methods. New York: John Wiley and Sons, Inc.Google Scholar
Kielar, A. & Joanisse, M. F. 2011. The role of semantic and phonological factors in word recognition: An ERP cross-modal priming study of derivational morphology. Neuropsychologia, 491, 161–177. DOI logoGoogle Scholar
Lenci, A. 2018. Distributional models of word meaning. Annual Review of Linguistics, 41, 151–171. DOI logoGoogle Scholar
Lenth, R. V. 2016. Least-squares means: The R package lsmeans. Journal of Statistical Software, 69(1), 1–33. DOI logoGoogle Scholar
Libben, G. 2010. Compound words, semantic transparency, and morphological transcendence. In S. Olsen, Ed., New impulses in word-formation, 212–232. Hamburg: Buske.Google Scholar
Lipka, L. 1977. Lexikalisierung, idiomatisierung und hypostasierung als probleme einer synchronischen wortbildungslehre. In H. E. Brekle & D. Kastovsky, Eds., Perspektiven der Wortbildungsforschung, 155–164. Bonn: Bouvier Verlag Herbert Grundmann.Google Scholar
1992. Lexicalization and institutionalization in English and German. Linguistica Pragensia/Akademie Ved CR, Ústav pro Jazyk Ceský, 1–13.Google Scholar
Longtin, C.-M., Segui, J. & A. H. P. 2003. Morphological priming without morphological relationship. Language and Cognitive Processes, 18(3), 313–334. DOI logoGoogle Scholar
Marelli, M. & Baroni, M. 2015. Affixation in semantic space: Modeling morpheme meanings with compositional distributional semantics. Psychological Review, 122(3), 485–515. DOI logoGoogle Scholar
Marslen-Wilson, W., Komisarjevsky Tyler, L., Waksler, R. & Oldername, L. 1994. Morphology and meaning in the English mental lexicon. Psychological Review, 101(1), 1–33. DOI logoGoogle Scholar
Meunier, F. & Segui, J. 1999. Frequency effects in auditory word recognition: The case of suffixed words. Journal of Memory and Language, 41(3), 327–344. DOI logoGoogle Scholar
Mikolov, T., Chan, K., Corrado, G. & Dean, J. 2013. Efficient estimation of word representations in vector space. In Proceedings of International Conference on Learning Representations (ICLR), Scottsdale.Google Scholar
Morris, J., Grainger, J. & Holcomb, P. J. 2013. Tracking the consequences of morpho-orthographic decomposition using ERPs. Brain Research, 15291, 92–104. DOI logoGoogle Scholar
Padó, S., Herbelot, A., Kisselew, M. & Šnajder, J. 2016. Predictability of distributional semantics in derivational word formation. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 1285–1296.Google Scholar
Park, J., Sana, F., Gagné, C. L. & Spalding, T. L. 2020. Is inhibition involved in the processing of opaque compound words? A study of individual differences. The Mental Lexicon, 15(2), 258–294. DOI logoGoogle Scholar
Pollatsek, A., Rayner, K. & Lee, H.-W. 2000. Chapter 15 - Phonological Coding in Word Perception and Reading. In A. Kennedy, R. Radach, D. Heller & J. Pynte, Eds., Reading as a perceptual process, 339–426. Elsevier. DOI logoGoogle Scholar
R Core Team 2015. R: A language and environment for statistical computing.Google Scholar
Rastle, K., Davis, M. H. & New, B. 2004. The broth in my brother’s brothel: Morpho-orthographic segmentation in visual word recognition. Psychonomic Bulletin & Review, 11(6), 1090–1098. DOI logoGoogle Scholar
Rayner, K. & Duffy, S. A. 1986. Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity. Memory & cognition, 14(3), 191–201. DOI logoGoogle Scholar
Reddy, S., McCarthy, D. & Manandhar, S. 2011. An empirical study on compositionality in compound nouns. In Proceedings of the 5th International Joint Conference on Natural Language Processing, 210–218. Chiang Mai, Thailand.Google Scholar
Ripley, B. D. 1996. Pattern Recognition and Neural Networks. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Roché, M. 2004. Mot construit ? Mot non construit ? Quelques réflexions à partir des dérivés en ‑ier(e). Verbum, 26(2), 459–480.Google Scholar
Sahlgren, M. & Lenci, A. 2016. The effects of data size and frequency range on distributional semantic models. arXiv preprint arXiv:1609.08293. DOI logoGoogle Scholar
Schäfer, R. & Bildhauer, F. 2012. Building large corpora from the web using a new efficient tool chain. In N. Calzolari, K. Choukri, T. Declerck, M. Uğur Doğan, B. Maegaard, J. Mariani, A. Moreno, J. Odijk & S. Piperidis, Eds., Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC’ 12), 486–493. Istanbul, Turkey.Google Scholar
Smolka, E. & Libben, G. 2017. ‘Can you wash off the hogwash?’ – semantic transparency of first and second constituents in the processing of german compounds. Language, Cognition and Neuroscience, 32(4), 514–531. DOI logoGoogle Scholar
Smolka, E., Libben, G. & Dressler, W. U. 2019. When morphological structure overrides meaning: evidence from german prefix and particle verbs. Language, Cognition and Neuroscience, 34(5), 599–614. DOI logoGoogle Scholar
Urieli, A. 2013. Robust French Syntax Analysis: reconciling statistical methods and linguistic knowledge in the Talismane toolkit. PhD thesis, University of Toulouse Jean Jaurès, Toulouse.
Varvara, R., Lapesa, G. & Padó, S. 2021. Grounding semantic transparency in context. Morphology, 311, 213–234. DOI logoGoogle Scholar
Venables, W. N. & Ripley, B. D. 2007. Modern Applied Statistics with S. New York: Springer.Google Scholar
Wauquier, M. 2020. Confrontation des procédés dérivationnels et des catégories sémantiques dans les modèles distributionnels. PhD thesis, Université Toulouse 2 – Jean Jaurès.
Cited by (1)

Cited by one other publication

Wauquier, Marine
2022. Apports de la sémantique distributionnelle pour la morphologie dérivationnelle. Corpus :23 DOI logo

This list is based on CrossRef data as of 5 july 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.