Eesti keele kui teise keele õpikute lausete analüüs ja selle rakendamine eri keeleoskustasemete sõnastike näitelausete automaatsel valikul
Analysis of CEFR-graded course book sentences and their use for automatic detection of good dictionary examples

Summary/Abstract: The aim of the study was to develop new Estonian GDEX configurations for A-, B- and C-language proficiency levels. GDEX (Good Dictionary Example) (Kilgarriff et al. 2008) is a software module of the corpus query system Sketch Engine (Kilgarriff et al. 2004), which helps to identify good dictionary example candidates from large corpora. In order to identify which specific parameters characterise sentences in each proficiency level, full sentences from the Estonian Coursebook Corpus 2018 were analysed using a program called Analyser of Sentence Parameters developed at the Institute of the Estonian Language. The analyser allows to find out how long the sentences and tokens are, what kind of verb forms are used, what syntactic properties the sentences have etc. The analysis showed that compared to the latest Estonian GDEX configuration 1.4 such parameters as sentence and token length, occurrence of certain verb forms and parts of speech needed to be adjusted. Accordingly, for A-level the sentence length was set to 3–14 tokens (optimal interval 4–7 tokens), for B-level 3–18 tokens (optimal interval 4–12) and for C-level 4–23 tokens (optimal interval 6–14 tokens). A new classifier that penalises tokens longer than 9 characters on A-level and tokens longer than 11 characters on B-level was introduced. On A- and B-levels certain verb forms were penalised or banned from appearing in the sentence. etSkELL – a corpus tool for Estonian language learning – and the dictionary portal Sõnaveeb (Wordweb) are introduced as possible ways to implement the new GDEX configurations output. The results of this paper can be applied in compiling corpora and teaching materials for different language proficiency levels.

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