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Talking about quantities in space: Vague quantifiers, context and similarity

Published online by Cambridge University Press:  11 March 2014

Kenny R. Coventry ,
Angelo Cangelosi ,
Stephen E. Newstead  and
Davi Bugmann
Kenny R. Coventry*
Affiliation:
Hanse Institute for Advanced Studies, Northumbria University
Angelo Cangelosi
Affiliation:
University of Plymouth
Stephen E. Newstead
Affiliation:
University of Plymouth
Davi Bugmann
Affiliation:
University of Plymouth
*
Correspondence addresses: Kenny R. Coventry, Cognition and Communication Research Centre, School of Life Sciences, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK. E-mail: kenny.coventry@northumbria.ac.uk
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Abstract

In this paper we examine how vague quantifiers, such as few, several, lots of, map onto non-linguistic number systems. In particular our focus is to examine how judgements about vague quantifiers are affected by the presence of objects in visual scenes other than those being referred to. An experiment is presented that manipulated the number of objects in a visual scene (men playing golf; the ‘focus’ objects) together with the number of other objects in those scenes and their similarity—in terms of form (women or crocodiles) and function (playing golf, not playing golf)—to the focus objects. We show that the number of other objects in a scene impacts upon quantifiers judgements even when those objects are in a different category to the focus objects. We discuss the results in terms of the mapping between the large approximate number (estimation) system and language.

Keywords

Quantifiersapproximate number systemvisual attentioncontext
Type
Research Article
Information
Language and Cognition , Volume 2 , Issue 2 , June 2010 , pp. 221 - 241
Copyright
Copyright © UK Cognitive Linguistics Association 2010

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References

Allen, J. 1987. Natural language understanding. Menlo Park, CA: Benjamin/Cummings.Google Scholar
Alshawi, H. 1990. Resolving quasi logical forms. Computational Linguistics 16. 133–144.Google Scholar
Barner, D., Chow, K. & Yang, S.-J.. 2009. Finding one's meaning: A test of the relation between quantifiers and integers in language development. Cognitive Psychology 58. 195–219.Google Scholar
Bass, B. M., Cascio, W. F. & O'Connor, E. J.. 1984. Magnitude estimations of frequency and amount. Journal of Applied Psychology 53. 313–320.Google Scholar
Cangelosi, A., Coventry, K., Rajapakse, R., Joyce, D., Bacon, A., Richards, L., Newstead, S.. 2005. Grounding language in perception: A connectionist model of spatial terms and vague quantifiers. In Cangelosi, A., Bugmann, G. & Borisyuk, R. (eds.), Modelling language, cognition and action: Proceedings of the 9th neural computation and psychology workshop, 47–56. Singapore: World Scientific.Google Scholar
Casasanto, D. 2005. Crying “Whorf”. Science 307. 1721–1722.Google Scholar
Chase, C. I. 1969. Often is where you find it. American Psychologist 24. 1043.Google Scholar
Condry, K. F. & Spelke, E. S.. 2008. The development of language and abstract concepts: The case of natural number. Journal of Experimental Psychology: General 137(1). 22–38.Google Scholar
Coventry, K. R., Cangelosi, A., Newstead, S. N., Bacon, A. & Rajapakse, R.. 2005a. Grounding natural language quantifiers in visual attention. In Bara, B. G., Barsalou, L. & Bucciarelli, M. (eds.), Proceedings of the 27th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Coventry, K. R., Cangelosi, A., Rajapakse, R., Bacon, A., Newstead, S., Joyce, D. & Richards, L. V.. 2005b. Spatial prepositions and vague quantifiers: Implementing the functional geometric framework. In Freksa, C., Knauff, M., Krieg-Bruckner, B. & Nebel, B. (eds.), Spatial cognition, volume IV. Reasoning, action and interaction, 98–110. Lecture notes in computer science. Berlin: Springer-Verlag.Google Scholar
Coventry, K. R., Cangelosi, A., Newstead, S., Rajapakse, R., Bugmann, D. & Bacon, A.. in preparation. Number estimation and talking about number bootstrap each other during learning.Google Scholar
Coventry, K. R. & Garrod, S. C.. 2004. Seeing, saying and acting. The psychological semantics of spatial prepositions. Hove: Psychology Press.Google Scholar
Cox, E. 2001. Fuzzy logic and the measures of certainty in eCommerce expert systems. PC AI 15(3). 16–22.Google Scholar
da Rosa, V. S., Beckenkamp, F. G. & Hoppen, N.. 1997. The application of fuzzy logic to model semantic variables in a hybrid model for classification expert system. In Steele, N. (ed.), ISFL'97. Second International ICSC Symposium on Fuzzy Logic and Applications, 301–7. Zurich: Academic Press.Google Scholar
Franceschini, F. & Romano, D.. 1999. Control chart for linguistic variables: A method based on the use of linguistic quantifiers. International Journal of Production Research 37(16). 3791–801.Google Scholar
Frank, M. C., Everett, D. L., Fedorenko, E. & Gibson, E.. 2008a. Number as cognitive technology: Evidence from Pirahã. Cognition 108. 818–824.Google Scholar
Frank, M. C., Fedorenko, E. & Gibson, E.. 2008b. Language as cognitive technology: English speakers match like Pirahã when you don't let them count. Proceedings of the 30th annual meeting of the Cognitive Science Society. 439–444.Google Scholar
Geurts, B., Katsos, N., Cummins, C., Moons, J. & Noordman, L.. 2010. Scalar quantifiers: Logic, acquisition and processing. Language and Cognitive Processes 25. 130–148.Google Scholar
Goocher, B. E. 1965. Effects of attitude and experience on the selection of frequency adverbs. Journal of Verbal Learning and Verbal Behavior 4. 193–195.Google Scholar
Gordon, P. 2004. Numerical cognition without words: Evidence from Amazonia. Science 306. 496–499.CrossRefGoogle ScholarPubMed
Halberda, J. & Feigenson, L. 2008. Developmental change in the acuity of the “Number Sense”: The approximate number system in 3-, 4-, 5-, 6-year-olds and adults. Developmental Psychology, 44(5). 1457–1465.Google Scholar
Halberda, J., Mazzocco, M. & Feigenson, L. 2008a. Individual differences in nonverbal number acuity predict maths achievement. Nature, 455. 665–668.Google Scholar
Halberda, J., Sires, S. F. & Feigenson, L.. 2006. Multiple spatially overlapping sets can be enumerated in parallel. Psychological Science 17(7). 572–576.Google Scholar
Halberda, J., Taing, L. & Lidz, J.. 2008b. The development of “Most” comprehension and its potential dependence on counting ability in preschoolers. Language Learning and Development 4(2). 99–121.Google Scholar
Hauser, M. D., Tsao, F., Garcia, P. & Spelke, E. S.. 2003. Evolutionary foundations of number: Spontaneous representation of numerical magnitudes by cotton-top tamarins. Proceedings of the Royal Society, London, B 270. 1441–1446.Google Scholar
Hormann, H. 1983. Then calculating listener, or how many are einige, mehrere and ein paar (some, several and a few). In Bauerle, R., Schwarze, C. & von Stechow, A. (eds.), Meaning, use and interpretation of language. Berlin: Mouton de Gruyter.Google Scholar
Hurewitz, F., Papafragou, A., Gleitman, L. & Gelman, R.. 2006. Asymmetries in the acquisition of numbers and quantifiers. Language Learning and Development 2. 77–96.Google Scholar
Inhelder, B. & Piaget, J.. 1958. La genèse des structures logiques élémentaires: Classifications et Sériations. Delachaux et Niestlé, Neuchâtel. [English translation published (1964): The early growth of logic in the child: Classification and seriation. Routledge and Kegan Paul, London].Google Scholar
Jager, R. R. 1995. Multicriteria decision making using fuzzy quantifiers. In Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering, 42–46. New York: IEEE.Google Scholar
Kacprzyk, J. 1999. Mining sales data at a computer retailer via fuzzy-logic-based linguistic. In Gedeon, T., Wong, P.et al. (eds.), ICONIP'99 6th International Conference on Neural Information Processing, 591–596. Piscataway, NJ: IEEE.Google Scholar
Mandler, G. & Shebo, B. J.. 1982. Subitizing: An analysis of its component processes. Journal of Experimental Psychology: General 111. 1–22.Google Scholar
Moxey, L. M. & Sanford, A. J.. 1993. Communicating quantities. A psychological perspective. Hove, East Sussex: Lawrence Erlbaum Associates.Google Scholar
Moxey, L. M., Sanford, A. J. & Dawydiak, E. J.. 2001. Denials as controllers of negative quantifier focus. Journal of Memory and Language 44. 427–442.Google Scholar
Newstead, S. E. & Collis, J.. 1987. Context and the interpretation of quantifiers of frequency. Ergonomics 30. 1447–1462.Google Scholar
Newstead, S. E. & Coventry, K. R.. 2000. The role of context and functionality in the interpretation of quantifiers. European Journal of Cognitive Psychology 12(2). 243–259.Google Scholar
Newstead, S. E. & Griggs, R. A.. 1984. Fuzzy quantifiers as an explanation of set inclusion performance. Psychological Research 46. 377–388.CrossRefGoogle Scholar
Newstead, S. E., Pollard, P. & Reizebos, D.. 1987. The effect of set size on the interpretation of quantifiers used in rating scales. Applied Ergonomics 18. 178–182.Google Scholar
Pica, P., Lemer, C., Izard, V. & Dehaene, S.. 2004. Exact and approximate arithmetic in an amazonian indigene group. Science 306(5695). 499–503.Google Scholar
Pietroski, P., Lidz, J., Hunter, T. & Halberda, J.. 2009. The meaning of ‘Most’: Semantics, numerosity and psychology. Mind and Language 24(5). 554–585.Google Scholar
Reyna, V. F. 1981. The language of possibility and probability: Effects of negation on meaning. Memory and Cognition 9. 642–650.Google Scholar
Saba, W. & Corriveau, J.-P.. 1997. A pragmatic treatment of quantification in natural language. Proceedings of the AAAI national conference on artificial intelligence and 9th innovative applications of artificial intelligence conference (AAAI97-IAAI97), 610–615.Google Scholar
Spencer, J. P., Blumberg, M. S., McMurray, B., Robinson, S. R., Samuelson, L. K. & Tomblin, J. B.. 2009. Short arms and talking eggs: Why we should no longer abide the nativist-empiricist debate. Child Development Perspectives 3(2). 79–87.Google Scholar
Trick, L. M. & Pylyshyn, Z.. 1993. What enumeration studies can show us about spatial attention: Evidence for preattentive processing. Journal of Experimental Psychology: Human Perception and Performance 19. 331–351.Google Scholar
Weining Zhang, Y. C., Reagan, B. & Nakajima, H.. 1995. Context-dependent interpretations of linguistic terms in fuzzy relational databases. In Yu, P. S. & Chen, A. L. P. (eds), Proceedings of the 11th International Conference on Data Engineering, 139–146. Taipei, Taiwan & Los Alamitos, CA: IEEE Computer Society Press.Google Scholar
Wright, D. B., Gaskell, G. D. & O'Muircheartaigh, C.. 1994. How much is “quite a bit”? Mapping between numerical quantities and vague quantifiers. Applied Cognitive Psychology 8. 479–496.Google Scholar
Xu, F., Spelke, E. S. & Goddard, S.. 2005. Number sense in human infants. Developmental Science 8(1). 88–101.Google Scholar