To drop or not to drop? Predicting the omission of the infinitival marker in a Swedish future construction

Author:

Berdicevskis Aleksandrs1,Coussé Evie2,Koplenig Alexander3,Adesam Yvonne1

Affiliation:

1. Språkbanken Text, Department of Swedish, Multilingualism, Language technology, University of Gothenburg , Gothenburg , Sweden

2. Department of Languages and Literatures , University of Gothenburg , Gothenburg , Sweden

3. Department of Lexical Studies , Leibniz-Institute for the German Language (IDS) , Mannheim , Germany

Abstract

Abstract We investigate the optional omission of the infinitival marker in a Swedish future tense construction. During the last two decades the frequency of omission has been rapidly increasing, and this process has received considerable attention in the literature. We test whether the knowledge which has been accumulated can yield accurate predictions of language variation and change. We extracted all occurrences of the construction from a very large collection of corpora. The dataset was automatically annotated with language-internal predictors which have previously been shown or hypothesized to affect the variation. We trained several models in order to make two kinds of predictions: whether the marker will be omitted in a specific utterance and how large the proportion of omissions will be for a given time period. For most of the approaches we tried, we were not able to achieve a better-than-baseline performance. The only exception was predicting the proportion of omissions using autoregressive integrated moving average models for one-step-ahead forecast, and in this case time was the only predictor that mattered. Our data suggest that most of the language-internal predictors do have some effect on the variation, but the effect is not strong enough to yield reliable predictions.

Funder

Swedish Research Council

Marcus and Amalia Wallenberg Foundation

Publisher

Walter de Gruyter GmbH

Subject

Linguistics and Language,Language and Linguistics

Reference65 articles.

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2. Adesam, Yvonne & Aleksandrs Berdicevskis. 2021. Part-of-speech tagging of Swedish texts in the neural era. In Proceedings of the 23rd Nordic conference on computational linguistics, NoDaLiDa. Available at: https://aclanthology.org/2021.nodalida-main.20/.

3. Akaike, Hirotugu. 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19(6). 716–723. https://doi.org/10.1109/TAC.1974.1100705.

4. Becketti, Sean. 2013. Introduction to time series using Stata, 1st edn. College Station, Tex: Stata Press.

5. Berdicevskis, Aleksandrs. 2020. Choosing a new dependency parser for Sparv. Technical report. Availbale at: https://github.com/spraakbanken/golddatatools/blob/master/report_parsing_20200603.pdf.

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