Publications

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.

Abstract

In a recent Cognition paper (Cognition 85 (2002) B21), Bornkessel, Schlesewsky, and Friederici report ERP data that they claim “show that online processing difficulties induced by word order variations in German cannot be attributed to the relative infrequency of the constructions in question, but rather appear to reflect the application of grammatical principles during parsing” (p. B21). In this commentary we demonstrate that the posited contrast between grammatical principles and construction (in)frequency as sources of parsing problems is artificial because it is based on factually incorrect assumptions about the grammar of German and on inaccurate corpus frequency data concerning the German constructions involved.

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.