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

This paper investigates the time and space complexity of word order computation in the psycholinguistically motivated grammar formalism of Performance Grammar (PG). In PG, the first stage of syntax assembly yields an unordered tree ('mobile') consisting of a hierarchy of lexical frames (lexically anchored elementary trees). Associated with each lexica l frame is a linearizer—a Finite-State Automaton that locally computes the left-to-right order of the branches of the frame. Linearization takes place after the promotion component may have raised certain constituents (e.g. Wh- or focused phrases) into the domain of lexical frames higher up in the syntactic mobile. We show that the worst-case time and space complexity of analyzing input strings of length n is O(n5) and O(n4), respectively. This result compares favorably with the time complexity of word-order computations in Tree Adjoining Grammar (TAG). A comparison with Head-Driven Phrase Structure Grammar (HPSG) reveals that PG yields a more declarative linearization method, provided that the FSA is rewritten as an equivalent regular expression.

Abstract

We present the design, implementation and simulation results of a psycholinguistic model of human syntactic processing that meets major empirical criteria. The parser operates in conjunction with a lexicalist grammar and is driven by syntactic information associated with heads of phrases. The dynamics of the model are based on competition by lateral inhibition ('competitive inhibition'). Input words activate lexical frames (i.e. elementary trees anchored to input words) in the mental lexicon, and a network of candidate 'unification links' is set up between frame nodes. These links represent tentative attachments that are graded rather than all-or-none. Candidate links that, due to grammatical or 'treehood' constraints, are incompatible, compete for inclusion in the final syntactic tree by sending each other inhibitory signals that reduce the competitor's attachment strength. The outcome of these local and simultaneous competitions is controlled by dynamic parameters, in particular by the Entry Activation and the Activation Decay rate of syntactic nodes, and by the Strength and Strength Build-up rate of Unification links. In case of a successful parse, a single syntactic tree is returned that covers the whole input string and consists of lexical frames connected by winning Unification links. Simulations are reported of a significant range of psycholinguistic parsing phenomena in both normal and aphasic speakers of English: (i) various effects of linguistic complexity (single versus double, center versus right-hand self-embeddings of relative clauses; the difference between relative clauses with subject and object extraction; the contrast between a complement clause embedded within a relative clause versus a relative clause embedded within a complement clause); (ii) effects of local and global ambiguity, and of word-class and syntactic ambiguity (including recency and length effects); (iii) certain difficulty-of-reanalysis effects (contrasts between local ambiguities that are easy to resolve versus ones that lead to serious garden-path effects); (iv) effects of agrammatism on parsing performance, in particular the performance of various groups of aphasic patients on several sentence types.