The Indexical Hypothesis describes how sentences become meaningful through grounding their interpretation in action. We develop support for the hypothesis by examining how people understand innovative denominal verbs, that is, verbs made from nouns and first encountered by participants within the experiment (e.g., to crutch). Experiments 1 and 2 demonstrated that different syntactic constructions provide scenes or goals that influence the meaning created for the innovative verbs. Experiment 3 used reading time to demonstrate that people also consider possible interactions with the objects underlying the verbs (i.e., the affordances of the objects) when creating meaning. Experiment 4 used a property verification procedure to demonstrate that the affordances derived from the objects depend on the situation-specific actions needed to complete the goal specified by the syntactic construction. Thus the evidence supports a specific type of interaction between syntax and semantics that leads to understanding: The syntax specifies a general scene, and the affordances of objects are used to specify the scene in detail sufficient to take action. © 2000 Academic Press Key Words: embodied cognition; construction grammar; sentence comprehension; denominal verbs. How sentences are understood is a central question. Theories of sentence comprehension can inform work on parsing (e.g., Frazier & Clifton, 1996; MacDonald, Pearlmutter, & Seidenberg,

This paper introduces an extension of distinctive-collocate analysis that takes into account grammatical structure and is specifically geared to investigating pairs of semantically similar grammatical constructions and the lexemes that occur in them. The method, referred to as `distinctive-collexeme analysis' identifies lexemes that exhibit a strong preference for one member of the pair as opposed to the other, and thus makes it possible to identify subtle distributional differences between the members of such a pair. The method can be applied in the context of what is sometimes referred to as `grammatical alternation' (e.g. the dative alternation), but it can also be applied to other choices provided by the grammar (such as the two future tense constructions in English). The method has two main applications. First, it can reveal subtle differences between seemingly synonymous constructions, many of which are difficult to identify on the basis of more traditional approaches. Second, it can be used to investigate the very notion of `alternation'; we show that many alternations are much more restricted than has hitherto been assumed, and thus confirm the claims of recent, non-derivational views of grammar

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This paper introduces an extension of collocational analysis that takes into account grammatical structure and is specifically geared to investigating the interaction of lexemes and the grammatical constructions associated with them. The method is framed in a construction-based approach to language, i.e. it assumes that grammar consists of signs (form-meaning pairs), and is thus not fundamentally different from the lexicon. The method is applied to linguistic expressions at various levels of abstraction (words, semi-fixed phrases, argument structures, tense, aspect and mood). The method has two main applications: first, to increase the adequacy of grammatical description by providing an objective way of identifying the meaning of a grammatical construction and determining the degree to which particular slots in it prefer or are restricted to a particular set of lexemes; second, to provide data for linguistic theory-building

How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning mechanisms that can grasp generalizations from examples of specific usages, and that exhibit patterns of behaviour over the course of learning similar to those in children. Early learning of verb argument structure is an area of language acquisition that provides an interesting testbed for such approaches due to the complexity of verb usages. A range of linguistic factors interact in determining the felicitous use of a verb in various constructions—associations between syntactic forms and properties of meaning, that form the basis for a number of linguistic and psycholinguistic theories of language. We present a computational model for the representation, acquisition, and use of verbs and constructions. Our Bayesian framework is founded on a novel view of constructions as a probabilistic association between syntactic and semantic features. The computational experiments reported here demonstrate the feasibility of learning general constructions, and their exceptions, from individual usages of verbs. The behaviour of the model over the timecourse of acquisition mimics in relevant aspects the stages of learning exhibited by children. Our proposal thus sheds light on the possible mechanisms at work in forming linguistic generalizations and maintaining knowledge of exceptions. 1

A thoroughly investigated area in syntactic research is what have often been considered transformationally related alternations; consider (1), (2) and (3) for examples of particle placement, dative shift and preposition stranding respectively. I

A neural network model of language acquisition is introduced, based on and motivated by current research in psychology and linguistics. It includes both semanticfeature representations of words and localist linguistic representations of words. The network learns to associate the semantic features of words to their linguistic labels, as well as to predict the next word in the corpus. This is interpreted to model both the acquisition of a lexicon, and the beginnings of syntax or grammar (word order). The relationship of lexical learning to grammar learning is examined, and similarities to the human data found. The results may provide support for the `Grammar from the Lexicon', or `emergent grammar' position.

Linguistic forms are shaped by forces operating on vastly different time scales. Some of these forces operate directly at the moment of speaking, whereas others accumulate over time in personal and social memory. Our challenge is to understand how forces with very different time scales mesh together in the current moment to determine the emergence of linguistic form.

English resultative expressions have been a major focus of research on the syntax-semantics interface. The present paper argues that a family of related constructions is required to account for their distribution. We demonstrate that a number of generalizations follow from the semantics of the constructions we posit: the syntactic argument structure of the sentence is predic ted by general principles of argument linking; the aspectual structure of the sentence is determined by the aspectual structure of the constructional subevent, which is in turn predictable from general principles correlating event structure with change, extension, motion, and paths. Finally, the semantics and syntax of resultatives explain the possibilities for temporal relations between the two subevents. At the same time that these generalizations clearly exist, there is also a great deal of idiosyncrasy involved in resultatives. Many idiosyncratic instances and small subclasses of the construction must be learned and stored individually. The account serves to justify aspects of what we share in our overall vision of grammar, what we might call the "constructional" view. To the extent that our treatment of the resultative can be stated only within the constructional view, it serves as evidence for this view as a whole. 1. A constructional view of grammar For fifteen years, the English resultative construction has been a focus of research on the syntaxsemantics interface. Each of us has made proposals about the resultative (Goldberg 1991; Goldberg 1995; Jackendoff 1997a; Jackendoff 1990) proposals that share a certain family resemblance. The present paper is an attempt to consolidate what our approaches have in common and to add some new wrinkles to our common understanding. Our larger purpose is ...

A neural network model of language acquisition is introduced, motivated by current research in psychology and linguistics. It uses both extra-linguistic perceptual features and symbolic representations of words. The network learns to auto-associate these inputs to their linguistic labels, as well as to predict the next word in the corpus. This is interpreted to model both the acquisition of a lexicon, and the beginnings of syntax or grammar (word order). Furthermore, the inclusion of the extralinguistic perceptual features is argued to be a form of direct developmental grounding in embodied concepts, which allows the later learning of more abstract concepts to be grounded indirectly in meaning through relations to the first words. Through this bootstrapping process, the entire network may be scalable to large vocabularies, and may bridge the gap between high-dimensional and embodied theories of meaning.