Interpreting quantification

Alternative readings of quantification are considered. The absence of an unequivocal translation into ordinary speech is noted. Some examples are cited which, in the opinion of the author, are a result of equivocal readings of quantification, or unnecessarily restrictive readings which obscure its primary function.     

Interpreting spatial language in image captions

The map as a tool for accessing data has become very popular in recent years, but a lot of data do not have the necessary spatial meta-data to allow for that. Some data such as photographs however have spatial information in their captions and if this could be extracted, then they could be made available via map-based interfaces. Towards this goal, we introduce a model and spatio-linguistic reasoner for interpreting the spatial information in image captions that is based upon quantitative data about spatial language use acquired directly from people. Spatial language is inherently vague, and both the model and reasoner have been designed to incorporate this vagueness at the quantitative level and not only qualitatively.     

Understanding natural language

This paper describes a computer system for understanding English. The system answers questions, executes commands, and accepts information in an interactive English dialog.     

Connectionist natural language parsing

The key developments of two decades of connectionist parsing are reviewed. Connectionist parsers are assessed according to their ability to learn to represent syntactic structures from examples automatically, without being presented with symbolic grammar rules. This review also considers the extent to which connectionist parsers offer computational models of human sentence processing and provide plausible accounts of psycholinguistic data. In considering these issues, special attention is paid to the level of realism, the nature of the modularity, and the type of processing that is to be found in a wide range of parsers.     

Reference to numbers in natural language

A common view is that natural language treats numbers as abstract objects, with expressions like the number of planets, eight, as well as the number eight acting as referential terms referring to numbers. In this paper I will argue that this view about reference to numbers in natural language is fundamentally mistaken. A more thorough look at natural language reveals a very different view of the ontological status of natural numbers. On this view, numbers are not primarily treated abstract objects, but rather ‘aspects’ of pluralities of ordinary objects, namely number tropes, a view that in fact appears to have been the Aristotelian view of numbers. Natural language moreover provides support for another view of the ontological status of numbers, on which natural numbers do not act as entities, but rather have the status of plural properties, the meaning of numerals when acting like adjectives. This view matches contemporary approaches in the philosophy of mathematics of what Dummett called the Adjectival Strategy, the view on which number terms in arithmetical sentences are not terms referring to numbers, but rather make contributions to generalizations about ordinary (and possible) objects. It is only with complex expressions somewhat at the periphery of language such as the number eight that reference to pure numbers is permitted.     

Feature integration in natural language concepts

Two experiments measured the joint influence of three key sets of semantic features on the frequency with which artifacts (Experiment 1) or plants and creatures (Experiment 2) were categorized in familiar categories. For artifacts, current function outweighed both originally intended function and current appearance. For biological kinds, appearance and behavior, an inner biological function, and appearance and behavior of offspring all had similarly strong effects on categorization. The data were analyzed to determine whether an independent cue model or an interactive model best accounted for how the effects of the three feature sets combined. Feature integration was found to be additive for artifacts but interactive for biological kinds. In keeping with this, membership in contrasting artifact categories tended to be superadditive, indicating overlapping categories, whereas for biological kinds, it was subadditive, indicating conceptual gaps between categories. It is argued that the results underline a key domain difference between artifact and biological concepts.     

Generalization from natural language text

Generalization and memory are part of natural language understanding. This paper describes a model of generalization that is part of a system for language understanding. the Integrated Partial Parser (IPP). The generalization process includes the retrieval of relevant examples from long-term memory so that the concepts to be created can be determined when new stories are read. Generalizations are analyzed as to their critical parts and evaluated in light of later evidence. The knowledge structures used and a number of examples of the system in operation are presented.     

Learning theory and natural language

Formal Learning Theory may be conceived as a means of relating theories of comparative grammar to studies of linguistic development. After a brief review of relevant concepts, the present paper surveys formal results within Learning Theory that suggest correponding constraints on linguistic theory. Particular attention is devoted to the question: How many possible natural languages are there?     

Computer understanding of natural language

The state of research in automatic natural language processing at Yale University is described. Five programs are discussed: SAM, FRUMP, PAM, TALESPIN, and POLITICS.     

Linear separability in superordinate natural language concepts

Two experiments are reported in which linear separability was investigated in superordinate natural language concept pairs (e.g., toiletry-sewing gear). Representations of the exemplars of semantically related concept pairs were derived in two to five dimensions using multidimensional scaling (MDS) of similarities based on possession of the concept features. Next, category membership, obtained from an exemplar generation study (in Experiment 1) and from a forced-choice classification task (in Experiment 2) was predicted from the coordinates of the MDS representation using log linear analysis. The results showed that all natural kind concept pairs were perfectly linearly separable, whereas artifact concept pairs showed several violations. Clear linear separability of natural language concept pairs is in line with independent cue models. The violations in the artifact pairs, however, yield clear evidence against the independent cue models.     

Interpreting the WPPSI subtests scores of language impaired children--a structural approach

The problem of characterising more specifically the cognitive requirements involved in subtests from standardised measures of intelligence represents a main problem in the research on exceptional populations. Seventy-five specifically language impaired (SLI) preschool children and 49 normally developing children were administered the Wechsler Preschool and Primary Scale of Intelligence (WPPSI). The scaled scores on the WPPSI were categorised according to Bannatyne's suggested regrouping to determine whether the pattern Spatial > Conceptual > Sequential could be observed in the data. The predicted pattern was only partially confirmed for language impaired children. The scaled scores on the WPPSI were then recategorized according to their structural complexity. Since structurally complex tasks contain more categories than the structurally simpler tasks, the pattern structurally Simple > Moderate > Complex was predicted and confirmed for language impaired children. Furthermore, it was hypothesized that the structurally Complex categories would discriminate better between language-impaired children and normally developing children than any other recoded categories. This hypothesis was confirmed. The low scores obtained by language impaired children on structurally Complex categories were interpreted as the result of capacity limitations in information processing rather than a deficit of any particular mental ability.