Assessing the impact of automatic dependency annotation on the measurement of phraseological complexity in L2 Dutch
The extraction of phraseological units operationalized in phraseological complexity measures (Paquot, 2019) relies on automatic dependency annotations, yet the suitability of annotation tools for learner language is often overlooked. In the present article, two Dutch dependency parsers, Alpino (van Noord, 2006) and Frog (van den Bosch et al., 2007), are evaluated for their performance in automatically annotating three types of dependency relations (verb + direct object, adjectival modifier, and adverbial modifier relations) across three proficiency levels of L2 Dutch. These observations then s... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2021 |
Verlag/Hrsg.: |
Kyle
Kristopher |
Schlagwörter: | dependency parsing / L2 Dutch / phraseological complexity / proficiency |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-29029596 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://hdl.handle.net/2078.1/243730 |
The extraction of phraseological units operationalized in phraseological complexity measures (Paquot, 2019) relies on automatic dependency annotations, yet the suitability of annotation tools for learner language is often overlooked. In the present article, two Dutch dependency parsers, Alpino (van Noord, 2006) and Frog (van den Bosch et al., 2007), are evaluated for their performance in automatically annotating three types of dependency relations (verb + direct object, adjectival modifier, and adverbial modifier relations) across three proficiency levels of L2 Dutch. These observations then serve as the basis for an investigation into the impact of automatic dependency annotation on phraseological sophistication measures. Results indicate that both learner proficiency and the type of dependency relation function as moderating factors in parser performance. Phraseological complexity measures computed on the basis of both automatic and manual dependency annotations demonstrate moderate to high correlations, reflecting a moderate to low impact of automatic annotation on subsequent analyses.