Updating the dictionary: Semantic change identification based on change in bigrams over time

  • Sanni Nimb Society for Danish Language and Literature, Copenhagen, Denmark
  • Nicolai Hartvig Sørensen Society for Danish Language and Literature, Copenhagen, Denmark
  • Henrik Lorentzen Society for Danish Language and Literature, Copenhagen, Denmark
Keywords: corpus statistics, bigrams, dictionary update, semantic change, Danish


We investigate a method of updating a Danish monolingual dictionary with new semantic information on already included lemmas in a systematic way, based on the hypothesis that the variation in bigrams over time in a corpus might indicate changes in the meaning of one of the words. The method combines corpus statistics with manual annotations. The first step consists in measuring the collocational change in a homogeneous newswire corpus with texts from a 14 year time span, 2005 through 2018, by calculating all the statistically significant bigrams. These are then applied to a new version of the corpus that is split into one sub-corpus per year. We then collect all the bigrams that do not appear at all in the first three years, but appear at least 20 times in the following 11 years. The output, a dataset of 745 bigrams considered to be potentially new in Danish, are double annotated, and depending on the annotations and the inter-annotator agreement, either discarded or divided into groups of relevant data for further investigation. We then carry out a more thorough lexicographical study of the bigrams in order to determine the degree to which they support the identification of new senses and lead to revised sense inventories for at least one of the words Furthermore we study the relation between the revisions carried out, the annotation values and the degree of inter-annotator agreement. Finally, we compare the resulting updates of the dictionary with Cook et al. (2013), and discuss whether the method might lead to a more consistent way of revising and updating the dictionary in the future.


Download data is not yet available.


DDO = Den Danske Ordbog [The Danish Dictionary]. Retrieved from https://ordnet.dk/ddo (17. 2. 2020)

Macmillan = Macmillan English Dictionary. Retrieved from https://www.macmillandictionary.com/ (17. 2. 2020)

Korpus.dsl.dk = Language Technology Resources for Danish. Retrieved from https://korpus.dsl.dk/resources.html

Cook, P., Lau, J. H., Rundell, M., McCarthy, D., & Baldwin, T. (2013). A lexicographic appraisal of an automatic approach for detecting new word-senses. In Electronic lexicography in the 21st century: thinking outside the paper. Proceedings of the eLex 2013 conference (pp. 49–65). Tallinn, Estonia.

Lorentzen, H. (2004). The Danish Dictionary at large: Presentation, Problems and Perspectives. In G. Williams & S. Vessier (Eds.), Proceedings of the 11th EURALEX International Congress (pp. 285–294). Lorient, France.

Mikolov, T., Sutskever, I, Chen, K., Corrado, G., & Dean, J. (2013). Distributed Representations of Words and Phrases and their Compositionality. In Advances in neural information processing systems 26. Retrieved from https://arxiv.org/abs/1310.4546

Norling-Christensen, O., & Asmussen, J. (1998). The Corpus of The Danish Dictionary. Lexikos (Afrilex Series) 8, 223–242.

Pollak, S., Gantar, P., & Arhar Holdt, Š. (2019). What’s New on the Internetz? Extraction and Lexical Categorization of Collocations in Computer-Mediated Slovene. In International Journal of Lexicography, 32(2), 184–206.

Řehůřek, R., & Sojka, P. (2010). Software Framework for Topic Modelling with Large Corpora. In Proceedings of LREC 2010 workshop New Challenges for NLP Frameworks (pp. 46–50). Valletta, Malta: University of Malta.

Řehůřek, R. (2020). models.phrases – Phrase (collocation) detection. Retrieved from https://radimrehurek.com/gensim/models/phrases.html (17. 2. 2020)

Tahmasebi, N., Borin, L., & Jatowt, A. (2018). Survey of Computational Approaches to Lexical Semantic Change [Preprint at ArXiv 2018]. Retrieved from https://arxiv.org/abs/1811.06278

Traugott, E. C. (2017). Semantic Change. Oxford Research Encyclopedias [Online publication]. doi: 10.1093/acrefore/9780199384655.013.323

How to Cite
NimbS., SørensenN. H., & LorentzenH. (2020). Updating the dictionary: Semantic change identification based on change in bigrams over time. Slovenščina 2.0: Empirical, Applied and Interdisciplinary Research, 8(2), 112-138. https://doi.org/10.4312/slo2.0.2020.2.112-138