Pinker, S. & Bloom, P. (1990). Natural language and natural selection. Behavioral and Brain Sciences 13

Automatically summarizing vast amounts of on-line quantitative data with a short natural language paragraph has a wide range of real-world applications. However, this specific task raises a number of difficult issues that are quite distinct from the generic task of language generation: conciseness, complex sentences, floating concepts, historical background, paraphrasing power and implicit content. In this thesis, I address these specific issues by proposing a new generation model in which a first pass builds a draft containing only the essential new facts to report and a second pass incrementally revises this draft to opportunistically add as many background facts as can fit within the space limit. This model requires a new type of linguistic knowledge: revision operations, which specifyies the various ways a draft can...

A framework for the qualitative representation of positional information in a two-dimensional space is presented. Qualitative representations use discrete quantity spaces, where a particular distinction is introduced only if it is relevant to the context being modeled. This allows us to build a flexible framework that accommodates various levels of granularity and scales of reasoning. Knowledge about position in large-scale space is commonly represented by a combination of orientation and distance relations, which we express in a particular frame of reference between a primary object and a reference object. While the representation of orientation comes out to be more straightforward, the model for distances requires that qualitative distance symbols be mapped to geometric intervals in order to be compared; this is done by defining structure relations that are able to handle, among others, order of magnitude relations; the frame of reference with its three components (distance system, s...

The term ‘ontology ’ has recently acquired a certain currency within the knowledge engineering community, especially in relation to the ARPA knowledge-sharing initiative (see Gruber (to appear), Mars (ed.) 1994, Guarino 1994, Guarino, Carrara and Giaretta 1994, 1994a). The term is used in a number of different senses, however, not all of them clear or mutually compatible. Here

Cognitive Science, whose genesis was interdisciplinary, shows signs of reverting to a disjoint collection of fields. This paper presents a compact, theory-free task that inherently requires an integrated solution. The basic problem is learning a subset of an arbitrary natural language from picture-sentence pairs. We describe a very specific instance of this task and show how it presents fundamental (but not impossible) challenges to several areas of cognitive science including vision, language, inference and learning. 1 Introduction touchstone (tuch' ston'). n. 1. a black siliceous stone used to test the purity of gold and silver by the color of the streak produced on it by rubbing it with either metal. 2. a test or criterion for the qualities of a thing. ---Syn. 2. standard, measure, model, pattern. Among the things that cognitive science has studied most are visual perception, language, inference, and learning [Posner, 1989]. However, these are often studied as if they were isolat...

Concepts are the elementary units of reason and linguistic meaning. They are conventional and relatively stable. As such, they must somehow be the result of neural activity in the brain. The questions are: Where? and How? A common philosophical position is that all concepts—even concepts about action and perception—are symbolic and abstract, and therefore must be implemented outside the brain’s sensory-motor system. We will argue against this position using (1) neuroscientific evidence; (2) results from neural computation; and (3) results about the nature of concepts from cognitive linguistics. We will propose that the sensory-motor system has the right kind of structure to characterise both sensory-motor and more abstract concepts. Central to this picture are the neural theory of language and the theory of cogs, according to which, brain structures in the sensory-motor regions are exploited to characterise the so-called “abstract ” concepts that constitute the meanings of grammatical constructions and general inference patterns.

Subjects read narratives describing directions of objects around a standing or reclimng observer, who was periodically reoriented. RTs were measured to identify which object was currently located beyond the observer's head, feet, front, back, fight, and left. When the observer was standing, head/feet RTs were fastest, followed by front/back and then right/left. For the reclining observer, front/back RTs were fastest, followed by head/feet and then right/left. The data support the spatial framework model, according to which space is conceptualized in terms of three axes whose accessibility depends on body asymmetries and the relation of the body to the world. The data allow rejection of the equiavailability model, according to which RTs to all directions are equal, and the mental transformation model, according to which RTs increase with angular disparity from front. Consider the following passage ("The Gambler, the Nun, and the Radio, " Hemingway, 1927, p. 41): Out of the window of the hospital you could see a field with tumbleweed coming out of the snow, and a bare clay butte.... From the other window, if the bed was turned, you could see the

Work in philosophy and psychology has argued for a dissociation between perceptuallybased similarity and higher-level rules in conceptual thought. Although such a dissociation may be justified at times, our goal is to illustrate ways in which conceptual processing is grounded in perception, both for perceptual similarity and abstract rules. We discuss the advantages, power and influences of perceptually-based representations. First, many of the properties associated with amodal symbol systems can be achieved with perceptually-based systems as well (e.g. productivity). Second, relatively raw perceptual representations are powerful because they can implicitly represent properties in an analog fashion. Third, perception naturally provides impressions of overall similarity, exactly the type of similarity useful for establishing many common categories. Fourth, perceptual similarity is not static but becomes tuned over time to conceptual demands. Fifth, the original motivation or basis for sophisticated cognition is often less sophisticated perceptual similarity. Sixth, perceptual simulation occurs even in conceptual tasks that have no explicit perceptual demands. Parallels between perceptual and conceptual processes suggest that many mechanisms typically associated

Standard Functional Unification Grammars (FUGs) provide a structurally guided top-down control regime for sentence generation. When using FUGs to perform content realization as a whole, including lexical choice, this regime is no longer appropriate for two reasons: (1) the unification of non-lexicalized semantic input with an integrated lexico-grammar requires mapping "floating" semantic elements which can trigger extensive backtracking and (2) lexical choice requires accessing external constraint sources on demand to preserve the modularity between conceptual and linguistic knowledge. We introduce two control tools that we have implemented for FUGs to address these limitations: bk-class, a form of dependency-directed backtracking to efficiently process "floating" constraints and external, a co-routine mechanism allowing a FUG to cooperate with external constraint sources during unification. We show how these tools complement the top-down regime of FUGs to control the whol...

This article presents a theory that inte~ates space-based and object-based approaches to visual attention. The theory puts together M. P. van Oeffelen and P. G. Vos's ( 1982, 1983) COntour DEtector (CODE) theory of perceptual grouping by proximity with C. Bundesen's (1990) theory of visual attention (TVA). CODE provides input to TVA, accounting for spatially based between-object selection, and TVA converts the input to output, accounting for feature- and category-based withinobject selection. CODE clusters nearby items into perceptual groups that are both perceptual objects and regions of space, thereby integrating object-based and space-based approaches to attention. The combined theory provides a quantitative account of the effects of grouping by proximity and dis~nce between items on reaction time and accuracy data in 7 empirical situations that shaped the current literature on visual spatial attention. For the last decade the attention literature has been embroiled in a debate over the nature of visual spatial attention that focuses on the "thing " that attention selects (e.g., Baylis &