TY - JOUR
T1 - Extracting prototypes from exemplars.
T2 - What can corpus data tell us about concept representation?
AU - Divjak, Dagmar
AU - Arppe, Antti
PY - 2013
Y1 - 2013
N2 - Over the past four decades, two distinct alternatives have emerged to rule-based models of how linguistic categories are stored and represented as cognitive structures, namely the prototype and exemplar theories. Although these models were initially thought to be mutually exclusive, shifts from one mechanism to the other have been observed in category learning experiments, bringing the models closer together. In this paper we implement a technique akin to varying abstraction modelling, that assumes intermediate abstraction processes to underlie category representations and categorization decisions; we do so using statistical techniques such as regression and clustering that linguists are familiar with. Using this model we simulate, on the basis of actual usage of Russian TRY verbs and Finnish THINK verbs as observed in corpora, how prototypes for near-synonymous verbs could be formed from concrete exemplars at different levels of abstraction using statistical techniques that track frequency distributions in input. In so doing, we take a closer look at the cognitive linguistic flirtation with multiple categorization theories, suggesting three improvements anchored in the fact that cognitive linguistics is a usage-based theory of language. Firstly, we show that language provides support for considering single prototype and full exemplar models as opposite ends along a continuum of abstraction. Secondly, we present a methodology that simulates how prototypes can be obtained from exemplars at more than one level of abstraction in a systematic and verifiable way. And thirdly, we illustrate our claims on the basis of work on verbs, denoting intangible events that are neither stable in nor independent of time and express relational concepts; this implies that verbs are more susceptible to their meanings being influenced by the concepts they relate.
AB - Over the past four decades, two distinct alternatives have emerged to rule-based models of how linguistic categories are stored and represented as cognitive structures, namely the prototype and exemplar theories. Although these models were initially thought to be mutually exclusive, shifts from one mechanism to the other have been observed in category learning experiments, bringing the models closer together. In this paper we implement a technique akin to varying abstraction modelling, that assumes intermediate abstraction processes to underlie category representations and categorization decisions; we do so using statistical techniques such as regression and clustering that linguists are familiar with. Using this model we simulate, on the basis of actual usage of Russian TRY verbs and Finnish THINK verbs as observed in corpora, how prototypes for near-synonymous verbs could be formed from concrete exemplars at different levels of abstraction using statistical techniques that track frequency distributions in input. In so doing, we take a closer look at the cognitive linguistic flirtation with multiple categorization theories, suggesting three improvements anchored in the fact that cognitive linguistics is a usage-based theory of language. Firstly, we show that language provides support for considering single prototype and full exemplar models as opposite ends along a continuum of abstraction. Secondly, we present a methodology that simulates how prototypes can be obtained from exemplars at more than one level of abstraction in a systematic and verifiable way. And thirdly, we illustrate our claims on the basis of work on verbs, denoting intangible events that are neither stable in nor independent of time and express relational concepts; this implies that verbs are more susceptible to their meanings being influenced by the concepts they relate.
UR - https://www.academia.edu/20374394/Extracting_prototypes_from_exemplars._What_can_corpus_data_tell_us_about_concept_representation
UR - http://eprints.whiterose.ac.uk/90780/
U2 - 10.1515/cog-2013-0008
DO - 10.1515/cog-2013-0008
M3 - Article
SN - 0936-5907
VL - 24
SP - 221
EP - 274
JO - Cognitive Linguistics
JF - Cognitive Linguistics
IS - 2
ER -