Volume 8 Issue 1 (2010)
DOI:10.1349/PS1.1537-0852.A.379
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Analogy Is an Implicit Universal Semantic Map
Comment on ‘Grammaticalization and Semantic Maps: Evidence
from Artificial Language Evolution’ by Remi van Trijp
(2010)
Michael Cysouw
Max Planck Institute for Evolutionary Anthropology,
Leipzig
Van Trijp (2010) convincingly shows that very little
linguistic information—or even none at all—is needed to produce
multifunctional linguistic markers. Although it still remains to be demonstrated
that the mechanisms used in his artificial world will lead to multifunctionality
and semantic maps which are similar to the semantic maps that are attested in
the “real” world, it is promising to see multifunctionality arising
without pre-established grammatical categories. Still, I disagree with van Trijp
about the nature of the mechanism that he uses to obtain multifunctionality,
namely analogical reasoning. In contrast to his claim, I think that this
mechanism should be considered an implicit universal semantic map. Even though
my impression is that this disagreement is only a matter of words rather than
one of content, I still think the issue is important enough to be clarified in
more detail.
In the last paragraph of Section 3.2, van Trijp writes that “the
algorithm for analogical reasoning […] does not implement an implicit
universal [semantic map]”.[1]
His algorithm for analogical reasoning provides the artificial agents with a
method to determine the similarity between sensory events. If each event is
conceived as a point in conceptual space, then the algorithm thus provides
structure among these points. Given enough artificially produced languages, I
expect that the lexicalizations of these points will (on average) replicate the
sensory similarity between the events.
To make this a bit more concrete, consider the two events van Trijp uses
to exemplify the analogical reasoning in his artificial world. He argues that by
analyzing the sensory information, an event ‘A pushes B’ can be
interpreted as being similar to an event ‘C walk-to D’ (note that I
am talking about the real event here, not the lexical expression to describe
them), and consequently, that the “pusher” A can be interpreted as
being similar to the “walker” C. Now, the fact that the algorithm
for analogical reasoning makes a suggestion for the similarity between these
roles should lead to a similar lexicalization of the roles of
‘pusher’ and ‘walker’ (on average, given many different
artificial languages). So, the analogical reasoning will be directly reflected
in the semantic map.
The abstract algorithm to determine similarity between sensory
perceptions is, of course, a rather different kind of semantic map than the
traditional graph structures as described in Haspelmath (2003). However, as I
have argued in my contribution to this issue (Cysouw 2010), the
“real” semantic map is a matrix of distances between events, and the
graph is only a visualization of the structure of this distance matrix. In this
construal of semantic maps, the algorithm as used by van Trijp is in fact a
metric on events. So, analogical reasoning is a metric that produces the
semantic map.
This way of looking at things could lead to the following research
strategy: an algorithm for analogical reasoning is proposed, and many different
artificial languages are developed on this basis. If these artificial languages
(on average) result in a distance matrix similar to what is found in real-world
languages, then this would suggest that the sensory analogy algorithm replicates
the human judgments. The world-wide diversity of languages might thus be useful
to falsify models of sensory interpretation.
References
Croft, William. 2003. Typology and universals, 2nd edition.
Cambridge: Cambridge University Press. (Cambridge Textbooks in
Linguistics).
Cysouw, Michael. 2010. Semantic maps as metrics on meaning.
Linguistic Discovery, this volume. doi:10.1349/ps1.1537-0852.a.346
Haspelmath, Martin. 2003. The geometry of grammatical meaning:
Semantic maps and cross-linguistic comparison. The new psychology of language:
Cognitive and functional approaches to language structure, ed. by Michael
Tomasello, vol. 2, 211-242. Mahwah, NJ: Erlbaum.
van Trijp, Remi. 2010. Grammaticalization and semantic maps:
Evidence from artificial language evolution. Linguistic Discovery, this
issue. doi:10.1349/ps1.1537-0852.a.355
Author's contact information:
Michael Cysouw
Department of Linguistics
Max Planck Institute for Evolutionary Anthropology
Deutscher Platz 6
04103 Leipzig
Germany
cysouw@eva.mpg.de
[1]In this quote, van
Trijp actually writes “conceptual space”, which I have replaced here
with “semantic map”. This difference is just a question of
terminology, as I have detailed in section 2 of my contribution to this issue
(Cysouw 2010). In my usage of terms (following Haspelmath 2003),
‘conceptual space’ refers to the (infinite and unstructured)
collection of everything that can be talked about, and ‘semantic
map’ is the structure among these functions/meanings. Van Trijp uses
Croft’s (2003:133-139) terminology, in which ‘conceptual
space’ is used for what Haspelmath calls ‘semantic
map’.
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