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RiYou4

Abstract:

The topic of this study is the prediction of aspectual coding asymmetries of verbs in Russian by the verbal feature Average Information Content. We employ the novel Topic Context Model that calculates the verbal information content from extra-sentential contexts i.e, the number of topics both in the target words’ larger discourses and their local discourses. The former are the corpus, the latter are docu- ments the target words occur in. In contrast to the study of Ko ̈lbl et al. (2020), TCM yielded disappointing results in this study. Our conclusion is that – compared to (Ko ̈lbl et al., 2020) – this is mainly due to the small number of local contexts we utilised.

Type: Misc

Year: 2020
Author:Michael Richter and Tariq Yousef
Title:Information from topic contexts: the prediction of aspectual coding of verbs in Russian
Month:November
@MISC{RiYou4,
YEAR = {2020},
AUTHOR = {Michael Richter and Tariq Yousef},
TITLE = {Information from topic contexts: the prediction of aspectual coding of verbs in Russian},
MONTH = {November}
}