Cover not available
Article published In:
International Journal of Corpus Linguistics
Vol. 27:3 (2022) ► pp.349–379

Use words, not constructions!

A new perspective on the unit of analysis in collostructional analysis

ORCID logo | Friedrich-Alexander-Universität Erlangen-Nürnberg

The aim of collostructional analysis or, more precisely, simple collexeme analysis, is to quantify the statistical association between a construction c and a lexeme l that occurs in a particular slot of the construction. The analysis is based on 2×2 contingency tables that ought to represent a cross-classification of the units of analysis. So far, the units of analysis have been identified either as all constructions in the corpus or all instances of a class C of constructions to which construction c belongs. In practice, it is often not possible or feasible to identify these constructions. Therefore, the sample size is typically approximated by heuristic estimates. The bottom-right cell of the contingency table is most affected by these approximations. I suggest that the units of analysis be defined on the word level, instead, as the class W of word forms that satisfy the restrictions on the collexeme slot of c.

Keywords: collostructional analysis, collexeme analysis, contingency table, unit of analysis, sample size
Article outline
  • 1.Introduction
    • 1.1Analysis of cooccurrence data with contingency tables
    • 1.2Collostructional analysis
  • 2.The unit of analysis in simple collexeme analysis
    • 2.1Constructions as the unit of analysis
    • 2.2Approximating the sample size
    • 2.3Problems arising from approximating the sample size
    • 2.4Practical impact of the approximations
  • 3.Suggested solution
  • 4.Discussion
    • 4.1Methodological advantages
    • 4.2Accidental application of word-based simple collexeme analysis
    • 4.3Change of interpretative perspective
  • 5.Word-based vs. heuristic simple collexeme analysis – Case studies
    • 5.1The [N waiting to happen] construction
    • 5.2The [X think nothing of V-ing] construction
  • 6.Conclusion
  • Notes
  • References
Published online: 25 May 2022
DOI logo
https://doi.org/10.1075/ijcl.20072.pro
References
Bybee, J.
(2010) Language, Usage and Cognition. Cambridge University Press. DOI logoGoogle Scholar
Chen, D., & Manning, C. D.
(2014) A fast and accurate dependency parser using neural networks. In A. Moschitti, B. Pang, & W. Daelemans (Eds.), Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP 2014) (pp. 740–750). DOI logoGoogle Scholar
Church, K. W.
(2000) Empirical estimates of adaptation: The chance of two Noriegas is closer to p/2 than p2 . In Proceedings of the 18th Conference on Computational Linguistics (COLING’00), Volume 1 (pp. 180–186). [URL]. DOI logo
Church, K. W., & Hanks, P.
(1990) Word association norms, mutual information, and lexicography. Computational Linguistics, 16 (1), 22–29.Google Scholar
Church, K., Gale, W., Hanks, P., & Hindle, D.
(1989) Parsing, word associations and typical predicate-argument relations. In Speech and Natural Language: Proceedings of a Workshop held at Cape Cod, Massachusetts, October 15–18, 1989 (pp. 75–81). [URL]. DOI logo
Evert, S.
(2004) The Statistics of Word Cooccurrences: Word Pairs and Collocations [Doctoral dissertation, Universität Stuttgart]. [URL]
Goldberg, A. E.
(2006) Constructions at Work: The Nature of Generalization in Language. Oxford University Press.Google Scholar
(2015) More (old and new) misunderstandings of collostructional analysis: On Schmid and Küchenhoff (2013). Cognitive Linguistics, 26 (3), 505–536. DOI logoGoogle Scholar
Gries, S. T., & Stefanowitsch, A.
(2004a) Covarying collexemes in the into-causative. In M. Achard & S. Kemmer (Eds.), Language, Culture, and Mind (pp. 225–236). CSLI.Google Scholar
(2004b) Extending collostructional analysis: A corpus-based perspective on “alternations”. International Journal of Corpus Linguistics, 9 (1), 97–129. DOI logoGoogle Scholar
Jones, S., & Sinclair, J.
(1974) English lexical collocations. Cahiers de Lexicologie, 24 1, 15–61.Google Scholar
Katz, S. M.
(1996) Distribution of content words and phrases in text and language modelling. Natural Language Engineering, 2 (1), 15–59. DOI logoGoogle Scholar
Kilgarriff, A.
(2005) Language is never, ever, ever, random. Corpus Linguistics and Linguistic Theory, 1 (2), 263–276. DOI logoGoogle Scholar
Korhonen, A.
(2002) Subcategorization Acquisition [Doctoral dissertation, University of Cambridge]. [URL]
Korhonen, A., Krymolowski, Y., & Briscoe, T.
(2006) A large subcategorization lexicon for natural language processing applications. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06) (pp. 1015–1020). [URL]
Küchenhoff, H., & Schmid, H.-J.
(2015) Reply to “More (old and new) misunderstandings of collostructional analysis: On Schmid & Küchenhoff” by Stefan Th. Gries. Cognitive Linguistics, 26 (3), 537–547. DOI logoGoogle Scholar
Loftus, G. R.
(1996) Psychology will be a much better science when we change the way we analyze data. Current Directions in Psychological Science, 5 (6), 161–171. DOI logoGoogle Scholar
Manning, C. D., Surdeanu, M., Bauer, J., Finkel, J. R., Bethard, S., & McClosky, D.
(2014) The Stanford CoreNLP natural language processing toolkit. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014, System Demonstrations (pp. 55–60). DOI logoGoogle Scholar
Nivre, J., Marneffe, M.-C. de, Ginter, F., Goldberg, Y., Hajič, J., Manning, C. D., McDonald, R., Petrov, S., Pyysalo, S., Silveira, N., Tsarfaty, R., & Zeman, D.
(2016) Universal Dependencies v1: A multilingual treebank collection. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16) (pp. 1659–1666). [URL]
Pecina, P.
(2005) An extensive empirical study of collocation extraction methods. In C. Callison-Burch & S. Wan (Eds.), Proceedings of the ACL Student Research Workshop (pp. 13–18). [URL]. DOI logo
(2010) Lexical association measures and collocation extraction. Language Resources and Evaluation, 44 (1), 137–158. DOI logoGoogle Scholar
Sarkar, A., & Zeman, D.
(2000) Automatic extraction of subcategorization frames for Czech. In Proceedings of the 18th International Conference on Computational Linguistics (COLING’00), Volume 2 (pp. 691–697). [URL]. DOI logo
Schäfer, R.
(2015) Processing and querying large web corpora with the COW14 architecture. In P. Bański, H. Biber, E. Breiteneder, M. Kupietz, H. Lüngen, & A. Witt (Eds.), Proceedings of the 3rd Workshop on Challenges in the Management of Large Corpora (CMLC-3) (pp. 28–34). [URL]
Schäfer, R., & Bildhauer, F.
(2012) Building large corpora from the web using a new efficient tool chain. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12) (pp. 486–493). [URL]
Schmid, H.-J.
(2000) English Abstract Nouns as Conceptual Shells: From Corpus to Cognition. Mouton de Gruyter. DOI logoGoogle Scholar
Schmid, H.-J., & Küchenhoff, H.
(2013) Collostructional analysis and other ways of measuring lexicogrammatical attraction: Theoretical premises, practical problems and cognitive underpinnings. Cognitive Linguistics, 24 (3), 531–577. DOI logoGoogle Scholar
Schuster, S., & Manning, C. D.
(2016) Enhanced English universal dependencies: An improved representation for natural language understanding tasks. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16) (pp. 2371–2378). [URL]
Stefanowitsch, A.
(2014) Collostructional analysis: A case study of the English into-causative. In T. Herbst, H.-J. Schmid, & S. Faulhaber (Eds.), Constructions Collocations Patterns (pp. 217–238). De Gruyter Mouton. DOI logoGoogle Scholar
Stefanowitsch, A., & Gries, S. T.
(2003) Collostructions: Investigating the interaction of words and constructions. International Journal of Corpus Linguistics, 8 (2), 209–243. DOI logoGoogle Scholar
(2005) Covarying collexemes. Corpus Linguistics and Linguistic Theory, 1 (1), 1–43. DOI logoGoogle Scholar
(2009) Corpora and grammar. In A. Lüdeling & M. Kytö (Eds.), Corpus Linguistics: An International Handbook (pp. 933–952). Walter de Gruyter.Google Scholar
Stevens, M. E., Giuliano, V. E., & Heilprin, L. B.
(Eds.) (1965) Statistical Association Methods for Mechanized Documentation. Symposium Proceedings. Washington 1964. National Bureau of Standards.Google Scholar
Uhrig, P., Evert, S., & Proisl, T.
(2018) Collocation candidate extraction from dependency-annotated corpora: Exploring differences across parsers and dependency annotation schemes. In P. Cantos-Gómez & M. Almela-Sánchez (Eds.), Lexical Collocation Analysis: Advances and Applications (pp. 111–140). Springer. DOI logoGoogle Scholar
Wiechmann, D.
(2008) On the computation of collostruction strength: Testing measures of association as expressions of lexical bias. Corpus Linguistics and Linguistic Theory, 4 (2), 253–290. DOI logoGoogle Scholar