Affiliation:
1. Freie Universität Berlin, Institut für Englische Philologie , Habelschwerdter Allee 45, 14195 Berlin , Germany
Abstract
Abstract
Lexical ambiguity in the English language is abundant. Word-class ambiguity is even inherently tied to the productive process of conversion. Most lexemes are rather flexible when it comes to word class, which is facilitated by the minimal morphology that English has preserved. This study takes a multivariate quantitative approach to examine potential patterns that arise in a lexicon where verb-noun and noun-verb conversion are pervasive. The distributions of three inflectional suffixes, verbal -s, nominal -s, and -ed are explored for their interaction with degrees of verb-noun conversion. In order to achieve that, the lexical dispersion, context-dependency, and lexical similarity between the inflected and bare forms were taken into consideration and controlled for in a Generalized Additive Models for Location, Scale and Shape (GAMLSS; Stasinopoulos, M. D., R. A. Rigby, and F. De Bastiani. 2018. “GAMLSS: A Distributional Regression Approach.” Statistical Modelling 18 (3–4): 248–73). The results of a series of zero-one-inflated beta models suggest that there is a clear “uncanny” valley of lexemes that show similar proportions of verbal and nominal uses. Such lexemes have a lower proportion of inflectional uses when textual dispersion and context-dependency are controlled for. Furthermore, as soon as there is some degree of conversion, the probability that a lexeme is always encountered without inflection sharply rises. Disambiguation by means of inflection is unlikely to play a uniform role depending on the inflectional distribution of a lexeme.
Subject
Literature and Literary Theory,Linguistics and Language,Language and Linguistics
Reference36 articles.
1. Beekhuizen, B., Armstrong, B. C., and Stevenson, S. (2021). Probing Lexical Ambiguity: Word Vectors Encode Number and Relatedness of Senses. Cognitive Science 45: 5, https://doi.org/10.1111/cogs.12943.
2. Bultena, S., Dijkstra, T., and van Hell, J. G. (2013). Cognate and Word Class Ambiguity Effects in Noun and Verb Processing. Language & Cognitive Processes 28(9): 1350–77, https://doi.org/10.1080/01690965.2012.718353.
3. Diessel, H. (2016). Frequency and Lexical Specificity in Grammar: A Critical Review. In: Heike, B., and Pfänder, S. (Eds.), Experience Counts: Frequency Effects in Language. De Gruyter, Berlin, pp. 209–38.
4. Dowle, M., and A. Srinivasan. 2021. Data.table: Extension of ‘Data.frame’. Also available at https://CRAN.R-project.org/package=data.table.
5. Du, J., F. Qi, and M. Sun. 2019. Using BERT for Word Sense Disambiguation. CoRR abs/1909.08358. Also available at http://arxiv.org/abs/1909.08358.