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Kempen, G., & Harbusch, K. (2019). Mutual attraction between high-frequency verbs and clause types with finite verbs in early positions: Corpus evidence from spoken English, Dutch, and German. Language, Cognition and Neuroscience, 34(9), 1140-1151. doi:10.1080/23273798.2019.1642498.
Abstract
We report a hitherto unknown statistical relationship between the corpus frequency of finite verbs and their fixed linear positions (early vs. late) in finite clauses of English, Dutch, and German. Compared to the overall frequency distribution of verb lemmas in the corpora, high-frequency finite verbs are overused in main clauses, at the expense of nonfinite verbs. This finite versus nonfinite split of high-frequency verbs is basically absent from subordinate clauses. Furthermore, this “main-clause bias” (MCB) of high-frequency verbs is more prominent in German and Dutch (SOV languages) than in English (an SVO language). We attribute the MCB and its varying effect sizes to faster accessibility of high-frequency finite verbs, which (1) increases the probability for these verbs to land in clauses mandating early verb placement, and (2) boosts the activation of clause plans that assign verbs to early linear positions (in casu: clauses with SVO as opposed to SOV order).Additional information
plcp_a_1642498_sm1530.pdf -
Kempen, G., & Harbusch, K. (2018). A competitive mechanism selecting verb-second versus verb-final word order in causative and argumentative clauses of spoken Dutch: A corpus-linguistic study. Language Sciences, 69, 30-42. doi:10.1016/j.langsci.2018.05.005.
Abstract
In Dutch and German, the canonical order of subject, object(s) and finite verb is ‘verb-second’ (V2) in main but ‘verb-final’ (VF) in subordinate clauses. This occasionally leads to the production of noncanonical word orders. Familiar examples are causative and argumentative clauses introduced by a subordinating conjunction (Du. omdat, Ger. weil ‘because’): the omdat/weil-V2 phenomenon. Such clauses may also be introduced by coordinating conjunctions (Du. want, Ger. denn), which license V2 exclusively. However, want/denn-VF structures are unknown. We present the results of a corpus study on the incidence of omdat-V2 in spoken Dutch, and compare them to published data on weil-V2 in spoken German. Basic findings: omdat-V2 is much less frequent than weil-V2 (ratio almost 1:8); and the frequency relations between coordinating and subordinating conjunctions are opposite (want >> omdat; denn << weil). We propose that conjunction selection and V2/VF selection proceed partly independently, and sometimes miscommunicate—e.g. yielding omdat/weil paired with V2. Want/denn-VF pairs do not occur because want/denn clauses are planned as autonomous sentences, which take V2 by default. We sketch a simple feedforward neural network with two layers of nodes (representing conjunctions and word orders, respectively) that can simulate the observed data pattern through inhibition-based competition of the alternative choices within the node layers. -
Kempen, G., & Vosse, T. (1992). A language-sensitive text editor for Dutch. In P. O’Brian Holt, & N. Williams (
Eds. ), Computers and writing: State of the art (pp. 68-77). Dordrecht: Kluwer Academic Publishers.Abstract
Modern word processors begin to offer a range of facilities for spelling, grammar and style checking in English. For the Dutch language hardly anything is available as yet. Many commercial word processing packages do include a hyphenation routine and a lexicon-based spelling checker but the practical usefulness of these tools is limited due to certain properties of Dutch orthography, as we will explain below. In this chapter we describe a text editor which incorporates a great deal of lexical, morphological and syntactic knowledge of Dutch and monitors the orthographical quality of Dutch texts. Section 1 deals with those aspects of Dutch orthography which pose problems to human authors as well as to computational language sensitive text editing tools. In section 2 we describe the design and the implementation of the text editor we have built. Section 3 is mainly devoted to a provisional evaluation of the system. -
Kempen, G. (1992). Generation. In W. Bright (
Ed. ), International encyclopedia of linguistics (pp. 59-61). New York: Oxford University Press. -
Kempen, G. (1992). Language technology and language instruction: Computational diagnosis of word level errors. In M. Swartz, & M. Yazdani (
Eds. ), Intelligent tutoring systems for foreign language learning: The bridge to international communication (pp. 191-198). Berlin: Springer. -
Kempen, G. (1992). Grammar based text processing. Document Management: Nieuwsbrief voor Documentaire Informatiekunde, 1(2), 8-10.
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Kempen, G. (1992). Second language acquisition as a hybrid learning process. In F. Engel, D. Bouwhuis, T. Bösser, & G. d'Ydewalle (
Eds. ), Cognitive modelling and interactive environments in language learning (pp. 139-144). Berlin: Springer.
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