Displaying 1 - 4 of 4
-
Levshina, N. (2023). Word classes in corpus linguistics. In E. Van Lier (
Ed. ), The Oxford handbook of word classes (pp. 833-850). Oxford: Oxford University Press. doi:10.1093/oxfordhb/9780198852889.013.34.Abstract
Word classes play a central role in corpus linguistics under the name of parts of speech (POS). Many popular corpora are provided with POS tags. This chapter gives examples of popular tagsets and discusses the methods of automatic tagging. It also considers bottom-up approaches to POS induction, which are particularly important for the ‘poverty of stimulus’ debate in language acquisition research. The choice of optimal POS tagging involves many difficult decisions, which are related to the level of granularity, redundancy at different levels of corpus annotation, cross-linguistic applicability, language-specific descriptive adequacy, and dealing with fuzzy boundaries between POS. The chapter also discusses the problem of flexible word classes and demonstrates how corpus data with POS tags and syntactic dependencies can be used to quantify the level of flexibility in a language. -
Levshina, N. (2022). Comparing Bayesian and frequentist models of language variation: The case of help + (to) Infinitive. In O. Schützler, & J. Schlüter (
Eds. ), Data and methods in corpus linguistics – Comparative Approaches (pp. 224-258). Cambridge: Cambridge University Press. -
Levshina, N. (2021). Conditional inference trees and random forests. In M. Paquot, & T. Gries (
Eds. ), Practical Handbook of Corpus Linguistics (pp. 611-643). New York: Springer. -
Gast, V., & Levshina, N. (2014). Motivating w(h)-Clefts in English and German: A hypothesis-driven parallel corpus study. In A.-M. De Cesare (
Ed. ), Frequency, Forms and Functions of Cleft Constructions in Romance and Germanic: Contrastive, Corpus-Based Studies (pp. 377-414). Berlin: De Gruyter.
Share this page