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Robust processing of the Dutch verb phrase

Bibliographic Data

ID21200027
AuthorsPaul Van Eecke (0000-0001-9153-9092, Vrije Universiteit Brussel, corresponding author)
Year2017
Volume9
Issue2
Pages226-250
Publication date2017-12-30
Open AccessNo
TypeARTICLE
VenueConstructions and Frames (JOURNAL)
Journal identifiersISSN: 1876-1933 • E-ISSN: 1876-1941
PublisherJohn Benjamins Publishing Company (PUBLISHER • NL)
DOI10.1075/cf.00003.van
OpenAlexW2780179821
LanguageEN
Citations received1
References cited8

The Dutch verb phrase (VP) is notorious for its syntactic intricacies. There are three main reasons why it is difficult to robustly handle its complexity in a processing model. First of all, a single VP can contain multiple modal auxiliaries (‘modal stacking’). Second, perfect auxiliaries can not only take a past participle as their argument but also a modal auxiliary in the infinitive form. Finally, there are various word orders in which the verb forms can appear. The first part of this paper presents a fully operational precision processing model of the Dutch VP in Fluid Construction Grammar. The model shows that the aforementioned challenges can be overcome by carefully managing the hierarchical relations between the elements of the VP. The second part introduces a robust comprehension method, which can process VPs containing morphological and word order errors. This method allows in many cases to recover the intended meaning of an erroneous VP, as well as to correct its form, using a strategy that exploits the deep semantic analyses and the bidirectional nature of the model

Exploit · Grammar · Infinitive · Linguistics · Modal · Modal verb · Natural language processing · Noun · Noun phrase · Participle · Phrase · Programming language · Verb · Verb phrase · Word order · Computer Science · Natural Language Processing Techniques · Speech and dialogue systems · Topic Modeling · Artificial Intelligence

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    Open Access•Martin J Pickering, Simon Garrod•Behavioral and Brain Sciences•2013

  • Do people use language production to make predictions during comprehension?

    Open Access•Martin J Pickering, Simon Garrod•Trends in Cognitive Sciences•2007

Citations per year0.33
Citation span2023 - 2023 (1)
Highly citedNo

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