1887
Volume 17, Issue 3
  • ISSN 1871-1340
  • E-ISSN: 1871-1375

Abstract

Abstract

This study addresses the relation between morphological productivity and semantic transparency. Using distributional semantics, we compare German word formation using particles with derivational word formation. We observed that derivational suffixes, but not particles, tend to make strong independent semantic contributions to their carrier words. In two-dimensional t-SNE maps, complex words show clustering by affix, but not by particle. Furthermore, the semantic vectors of suffixed words are predictable from their base words with higher accuracy than is possible for particle verbs. For particle verbs, but not affixed verbs, semantic similarity within the set of complex words correlated negatively with the number of types. Furthermore, only for particle verbs, a greater number of observed types predicted a reduced probability of observing unseen types. We propose that particle verbs primarily serve the onomasiological function of labeling, resulting in relatively idiosyncratic semantic vectors. By contrast, words sharing derivational affixes form distinct clusters in semantic space while maintaining strong and consistent semantic relations with their base words. This enables these words to serve not only as labels, but also allows them to be used with an anaphoric function in discourse.

Available under the CC BY 4.0 license.
Loading

Article metrics loading...

/content/journals/10.1075/ml.22012.stu
2023-03-23
2024-12-07
Loading full text...

Full text loading...

/deliver/fulltext/ml.22012.stu.html?itemId=/content/journals/10.1075/ml.22012.stu&mimeType=html&fmt=ahah

References

  1. Aronoff, M.
    (1976) Word Formation in Generative Grammar. MIT Press, Cambridge, Mass.
    [Google Scholar]
  2. Baayen, R. H.
    (1993) On frequency, transparency, and productivity. InBooij, G. E. and van Marle, J., editors, Yearbook of Morphology 1992, pages181–208. Kluwer Academic Publishers, Dordrecht. 10.1007/978‑94‑017‑3710‑4_7
    https://doi.org/10.1007/978-94-017-3710-4_7 [Google Scholar]
  3. (2001) Word Frequency Distributions. Kluwer Academic Publishers, Dordrecht. 10.1007/978‑94‑010‑0844‑0
    https://doi.org/10.1007/978-94-010-0844-0 [Google Scholar]
  4. (2005) Data mining at the intersection of psychology and linguistics. InCutler, A., editor, Twenty-first century psycholinguistics: Four cornerstones, pages69–83. Erlbaum, Hillsdale, New Jersey.
    [Google Scholar]
  5. Baayen, R. H., Chuang, Y.-Y., Shafaei-Bajestan, E., and Blevins, J.
    (2019) The discriminative lexicon: A unified computational model for the lexicon and lexical processing in comprehension and production grounded not in (de)composition but in linear discriminative learning. Complexity. 10.1155/2019/4895891
    https://doi.org/10.1155/2019/4895891 [Google Scholar]
  6. Baayen, R. H. and Lieber, R.
    (1991) Productivity and English derivation: a corpus-based study. Linguistics, 291:801–843. 10.1515/ling.1991.29.5.801
    https://doi.org/10.1515/ling.1991.29.5.801 [Google Scholar]
  7. Baayen, R. H. and Neijt, A.
    (1997) Productivity in context: a case study of a Dutch suffix. Linguistics, 35:565–587. 10.1515/ling.1997.35.3.565
    https://doi.org/10.1515/ling.1997.35.3.565 [Google Scholar]
  8. Baayen, R. H. and Renouf, A.
    (1996) Chronicling The Times: Productive Lexical Innovations in an English Newspaper. Language, 721:69–96. 10.2307/416794
    https://doi.org/10.2307/416794 [Google Scholar]
  9. Bojanowski, P., Grave, E., Joulin, A., and Mikolov, T.
    (2017) Enriching word vectors with subword information. Transactions of the Association for Computational Linguistics, 51:135–146. 10.1162/tacl_a_00051
    https://doi.org/10.1162/tacl_a_00051 [Google Scholar]
  10. Bonami, O. and Paperno, D.
    (2018) Inflection vs. derivation in a distributional vector space. Lingue e Linguaggio, 17(2):173–195.
    [Google Scholar]
  11. Booij, G.
    (1977) Dutch morphology: A study of word formation in generative grammar. 10.1515/9783112327708
    https://doi.org/10.1515/9783112327708 [Google Scholar]
  12. Booij, G. E.
    (2002) The morphology of Dutch. Oxford University Press, Oxford.
    [Google Scholar]
  13. (2016) Construction morphology. InHippisley, A. and Stump, G., editors, The Cambridge Handbook of Morphology, pages424–448. Cambridge University Press, Cambridge. 10.1017/9781139814720.016
    https://doi.org/10.1017/9781139814720.016 [Google Scholar]
  14. Chuang, Y., Brown, D., Evans, R., and Baayen, R. H.
    (2022) Paradigm gaps are associated with weird “distributional semantics” properties: Russian defective nouns and their case and number paradigms. The Mental Lexicon. 10.1075/ml.22013.chu
    https://doi.org/10.1075/ml.22013.chu [Google Scholar]
  15. Corbin, D.
    (1987) Morphologie derivationelle et structuration du lexique. Niemeyer, Tübingen.
    [Google Scholar]
  16. Dressler, W. U., & Ladányi, M.
    (2000) Productivity in word formation (WF): A morphological approach. Acta Linguistica Hungarica, 471, 103–145. 10.1023/A:1014010530824
    https://doi.org/10.1023/A:1014010530824 [Google Scholar]
  17. Dressler, Wolfgang
    (2003) Morphological Typology and First Language Acquisition: Some Mutual Challenges. CitetononCRdoi:10.26220/mmm.2360
    https://doi.org/Cite to nonCR doi: 10.26220/mmm.2360 [Google Scholar]
  18. Fernández-Domínguez, Jesús
    (2009) Productivity in English word-formation. An approach to N+N compounding.
    [Google Scholar]
  19. Good, I. J.
    (1953) The population frequencies of species and the estimation of population parameters. Biometrika, 401:237–264. 10.1093/biomet/40.3‑4.237
    https://doi.org/10.1093/biomet/40.3-4.237 [Google Scholar]
  20. Güunther, F. and Marelli, M.
    (2019) Enter sandman: Compound processing and semantic transparency in a compositional perspective. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(10):1872.
    [Google Scholar]
  21. Kastovsky, D.
    (1986) Productivity in word formation. Linguistics, 241:585–600. 10.1515/ling.1986.24.3.585
    https://doi.org/10.1515/ling.1986.24.3.585 [Google Scholar]
  22. Kempcke, G.
    (1965) Die Bedeutungsgruppen der verbalen Kompositionspartikeln an-und auf-in synchronischer und diachronischer Sicht. Beiträge zur Geschichte der deutschen Sprache und Literatur, volume 87.
    [Google Scholar]
  23. Kisselew, M., Padó, S., Palmer, A., and Snajder, J.
    (2015) Obtaining a better understanding of distributional models of german derivational morphology. InProceedings of the 11th International Conference on Computational Semantics, pages58–63.
    [Google Scholar]
  24. Kliche, F.
    (2009) Zur Semantik der Partikelverben auf ab. Eine Studie im Rahmen der Diskursepräentationstheorie. PhD thesis, Master’s thesis, Universität Tübingen.
    [Google Scholar]
  25. Köper, M., Schulte im Walde, S., Kisselew, M., and Padó, S.
    (2016) Improving zero-shot-learning for german particle verbs by using training-space restrictions and local scaling. InProceedings of the Fifth Joint Conference on Lexical and Computational Semantics, pages91–96. 10.18653/v1/S16‑2010
    https://doi.org/10.18653/v1/S16-2010 [Google Scholar]
  26. Krijthe, J. H.
    (2015) Rtsne: T-Distributed Stochastic Neighbor Embedding using Barnes-Hut Implementation. R package version 0.15.
    [Google Scholar]
  27. Lakoff, G. and Johnson, M.
    (1980) Metaphors we live by. University of Chicago Press, Chicago.
    [Google Scholar]
  28. Landauer, T. and Dumais, S.
    (1997) A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction and representation of knowledge. Psychological Review, 104(2):211–240. 10.1037/0033‑295X.104.2.211
    https://doi.org/10.1037/0033-295X.104.2.211 [Google Scholar]
  29. Lechler, A. and Roßdeutscher, A.
    (2009) Analysing german verb-particle constructions with’ auf ’within a drt based framework. 10.46771/2366077500220_2
    https://doi.org/10.46771/2366077500220_2 [Google Scholar]
  30. Lieber, R.
    (2010) Introducing Morphology. Cambridge University Press, Cambridge, UK.
    [Google Scholar]
  31. Lieber, R. and Baayen, R. H.
    (1993) Verbal prefixes in Dutch: a study in lexical conceptual structure. InBooij, G. E. and Marle, J. V., editors, Yearbook of Morphology 1993, pages51–78. Kluwer Academic Publishers, Dordrecht. 10.1007/978‑94‑017‑3712‑8_3
    https://doi.org/10.1007/978-94-017-3712-8_3 [Google Scholar]
  32. Maaten, L. V. D. and Hinton, G.
    (2008) Visualizing data using t-sne. Journal of machine learning research, 91(Nov):2579–2605.
    [Google Scholar]
  33. Marelli, M. and Baroni, M.
    (2015) Affixation in semantic space: Modeling morpheme meanings with compositional distributional semantics. Psychological Review, 122(3):485. 10.1037/a0039267
    https://doi.org/10.1037/a0039267 [Google Scholar]
  34. Möollemann, R.
    (2016) Implications of german word formation processes for a role and reference grammar approach to morphology. MA thesis, University of Düusseldorf.
    [Google Scholar]
  35. Nikolaev, A., Chuang, Y.-Y., and Baayen, R. H.
    (2022) A generating model for finnish nominal inflection using distributional semantics. under revision for the Mental Lexicon. 10.31234/osf.io/ndtv2
    https://doi.org/10.31234/osf.io/ndtv2 [Google Scholar]
  36. Plag, I.
    (1999) Morphological productivity: structural constraints in English derivation (Topics in English Linguistics 28). Berlin & New York: Mouton de Gruyter. 10.1017/S0022226701008982
    https://doi.org/10.1017/S0022226701008982 [Google Scholar]
  37. (2003) Word Formation in English. Cambridge University Press, Cambridge, UK. 10.1017/CBO9780511841323
    https://doi.org/10.1017/CBO9780511841323 [Google Scholar]
  38. Riddle, E.
    (1985) A historical perspective on the productivity of the suffixes -ness and -ity. InFisiak, J., editor, Historical Semantics, Historical Word-Formation, pages435–461. Mouton, New York. 10.1515/9783110850178.435
    https://doi.org/10.1515/9783110850178.435 [Google Scholar]
  39. Schreuder, R. and Baayen, R. H.
    (1994) Prefix-stripping re-revisited. Journal of Memory and Language, 331:357–375. 10.1006/jmla.1994.1017
    https://doi.org/10.1006/jmla.1994.1017 [Google Scholar]
  40. Schultink, H.
    (1961) Produktiviteit als Morfologisch Fenomeen. Forum der Letteren21, 110–125.
    [Google Scholar]
  41. Shafaei-Bajestan, E., Moradipour-Tari, M., Uhrig, P., and Baayen, R. H.
    (2022a) Semantic properties of english nominal pluralization: Insights from word embeddings. arXiv preprint arXiv:2203.15424.
    [Google Scholar]
  42. (2022b) Semantic properties of English nominal pluralization: Insights from word embeddings. arXiv arxiv. org/abs/ 2203. 15424v1.
    [Google Scholar]
  43. Shafaei-Bajestan, E., Uhrig, P., and Baayen, R. H.
    (2022c) Making sense of spoken plurals. Under revision for the Mental Lexicon. 10.1075/ml.22011.sha
    https://doi.org/10.1075/ml.22011.sha [Google Scholar]
  44. Shahmohammadi, H., Lensch, H., and Baayen, R. H.
    (2021) Learning zero-shot multifaceted visually grounded word embeddings via multi-task training. CoNLL 2021. arXiv preprint arXiv:2104.07500. 10.18653/v1/2021.conll‑1.12
    https://doi.org/10.18653/v1/2021.conll-1.12 [Google Scholar]
  45. Shen, T. and Baayen, H. R.
    (2022) Productivity and semantic transparency: An exploration of word formation in Mandarin Chinese. The Mental Lexicon.
    [Google Scholar]
  46. Shen, T. and Baayen, R. H.
    (2021) Adjective-noun compounds in Mandarin: a study on productivity. Corpus Linguistics and Linguistic Theory.
    [Google Scholar]
  47. Springorum, S., Utt, J., and Im Walde, S. S.
    (2013) Regular meaning shifts in german particle verbs: A case study. InProceedings of the 10th International Conference on Computational Semantics (IWCS 2013)-Long Papers, pages228–239.
    [Google Scholar]
/content/journals/10.1075/ml.22012.stu
Loading
/content/journals/10.1075/ml.22012.stu
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): embeddings; German; particle verbs; productivity; semantic transparency; suffixation
This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error