A Self‐Organizing Approach to Subject–Verb Number Agreement

Abstract

We present a self-organizing approach to sentence processing that sheds new light on notional plurality effects in agreement attraction, using pseudopartitive subject noun phrases (e.g., a bottle of pills). We first show that notional plurality ratings (numerosity judgments for subject noun phrases) predict verb agreement choices in pseudopartitives, in line with the "Marking" component of the Marking and Morphing theory of agreement processing. However, no account to date has derived notional plurality values from independently needed principles of language processing. We argue on the basis of new experimental evidence and a dynamical systems model that the theoretical black box of notional plurality can be unpacked into objectively measurable semantic features. With these semantic features driving structure formation (and hence agreement choice), our model reproduces the human verb production patterns as a byproduct of normal processing. Finally, we discuss how the self-organizing approach might be extended to other agreement attraction phenomena.

Encoding and Retrieval Interference in Sentence Comprehension: Evidence from Agreement

“…First, we describe a way that a cue-based retrieval memory model like ACT-R ( Lewis and Vasishth, 2005 ) can be augmented to account for the encoding effects we have observed. We then explain how a parsing model based on self-organization ( Kempen and Vosse, 1989 ; Vosse and Kempen, 2000 ; Tabor and Hutchins, 2004 ; Van der Velde and de Kamps, 2006 ; Smith et al, in press ), implements retrieval and encoding interference, and arguing that unlike ACT-R, the self-organizing approach naturally captures encoding interference effects a consequence of its main structure-building mechanism, and hence offers a more parsimonious explanation. 8…”

“…We propose that encoding interference can be captured in ACT-R by an additional mechanism we will refer to as activation leveling , responsible for equalizing the activation levels of elements sharing a feature. The second model is a self-organized parsing model (SOSP, Tabor and Hutchins, 2004 ; Smith et al, in press ) in which both encoding and retrieval interference follow from general feature-based structure building principles. This model thus has the advantage of capturing both types of interference through the same mechanism.…”

Hierarchical structure and memory retrieval mechanisms in agreement attraction

“…To reach that goal, we designed two experiments on the processing of sentences in a semi-artificial jabberwocky language in which pseudo-nouns replaced nouns, while function words and verbs were real words of the French language. The aim of using jabberwocky was to explore the influence of structural factors on memory, and control for semantic influences on attraction, given the known influence of semantic factors like the notional plurality of the sentence (e.g., Eberhard, 1999;Foote & Bock, 2012;Smith, Franck, & Tabor, 2018;Vigliocco, Butterworth & Garrett, 1996), but also the semantic similarity between the subject and the attractor (Barker, Nicol & Garrett, 2001) and the semantic plausibility of the attractor as being an agent (Hupet, Fayol, & Schelstraete, 1998). Using pseudo-nouns while preserving verbs and the grammatical skeleton of natural sentences prevents participants from building a rich semantic representation for the sentence while still allowing them to build a parse tree and computing the agreement dependency without difficulty.…”

“…In contrast, attraction is virtually nonexistent when the head and attractor have distinct morphological case markers (Badecker & Kuminiak, 2007;Lorimor et al, 2008;Malko & Slioussar, 2013;Marusic et al, 2013). With respect to semantic similarity, some studies have shown that attractors with a high overlap of semantic features with the subject head, in terms of animacy or in terms of semantic field (e.g., The canoe by the sailboats) trigger more attraction than those with a lower overlap (e.g., The canoe by the cabins, Barker et al, 2001;Smith, Franck & Tabor, 2018).…”

“…An important part of the literature on attraction has been concerned with the influence of semantics. Most of the research has focused on the role of the notional representation of the subject phrase (Eberhard, 1999;Foote & Bock, 2012;(Smith et al, 2018) Vigliocco, Butterworth & Garrett, 1996, and on the influence of semantic correlates of grammatical number and gender features (e.g., Bock, Nicol, & Cutting, 1999 ;Vigliocco & Franck, 2001).…”