Volume 8 Issue 1 (2010)
DOI:10.1349/PS1.1537-0852.A.374
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What Semantic Maps Show and What They Are Good for
Author’s reply to ‘Three Questions about Analyzing
Semantic Maps’ (Wälchli 2010b) and ‘Optimizing classical
maps’ (Narrog 2010)
Andrej L. Malchukov
Max Planck Institute for Evolutionary Anthropology,
Leipzig
In their commentaries, Heiko Narrog and Bernhard
Wälchli raise interesting questions with the approach I am advocating in my
paper. I will start with Bernhard Wälchli’s commentary, since it is
more on a critical note, and thus requires a more elaborate response.
The main goal of my paper was to question the general
assumption commonly underlying semantic maps that recurrent similarities should
always reflect semantic affinities; as pointed out, some of the similarities can
be attributed to other factors. A secondary goal was to show what consequences
this observation has for the semantic map approach. In his comment, Bernhard
Wälchli (2010b) does not challenge the actuality of these other factors,
but casts doubt on the validity of these findings for the methodology of
semantic maps. I will briefly react to the three questions raised by
Wälchli here.
1. Wouldn’t It Be Better
to Control for Noise Rather Than Exclude It?
First, I never meant to say that one should exclude
undesirable effects from a semantic map, but rather conflicting factors—I
thought the paper was quite explicit in that (see e.g. its concluding section):
one should feature out interfering factors (such as zero coding, marked forms of
oppositions, etc.) and thus try to get a clearer pattern on the semantic map. In
practice, this can be done either through delimiting the domain of investigation
from the very beginning, or by coding the relevant factor consistently in the
database, so that the impact of this factor can be controlled. For example, one
could restrict the investigation from the outset to overt markers (which would
also account for violations on the map of case markers discussed in section 6 of
my paper), to simplex (one-word) gram markers (which would also account for
contiguity violations caused by
te=iru form discussed in section 6.3), or
exclude grammatical categories related to lexical ones (which would also account
for the anomalous polysemy pattern of the
ma form in Teiwa discussed in
section 6.1).[1]
Alternatively, one
could control for the impact of these factors through their consistent coding in
the dataset (e.g. zero vs. overt markers, simplex vs. complex markers, markers
with/without lexical counterparts, etc.). Generally, I would agree with
Wälchli that the second approach is preferable, although it is also more
time-consuming. In my paper, I argued that one could get a clearer pattern/trend
on a semantic map when these interfering factors are controlled for. But in
order to do this, such confounding factors first need to be identified, which I
did by studying the rare/exceptional polyfunctionality patterns. On the one
hand, Wälchli seems to agree with me when he writes about desirability of
controlling for the impact of these factors (through the use of statistical
methods). On the other hand, however, he writes: “But wouldn’t it be
better to apply more robust methods for building semantic maps where a little
noise does not do any harm?” If this is meant as a suggestion that no
further analysis of similarity maps is needed or intended, I tend to disagree.
It seems that similarity maps for many domains, if taken at face value, reveal
few non-trivial generalizations, and such an approach definitely does not bring
us any further in understanding the motivations behind certain patterns (for
such an understanding, both general trends as well as exceptions/noise are
important, as I argued). Wälchli writes further: “The emerging
picture in probabilistic maps is not ‘messy’ because the method is
messy, but rather because this method can be applied to datasets which come
closer to reflecting the real amount of diversity in discourse.” Clearly,
semantic maps are of little use if we just find random variation. They are
valuable to the extent to which they visualize certain patterns, and the aim of
my article was to suggest how to refine the emerging factors on similarity maps
through control of confounding factors.
2. How Are Preselected Functions
Defined?
The issue of how categories/functions are identified within
languages as well as cross-linguistically is a general challenge for linguistic
research which shall not be addressed here (but see Haspelmath 2007 for
proposals). The selection of functions is subjective and depends ultimately on
the focus of investigation. It is conventional to specify
(“sharpen”) the functions under discussion through the use of
examples, which are designed to illustrate the functional properties of the
category under consideration. This is especially pressing for less conventional
categories (such as Companion in Wälchli 2010a), but it is also important
for categories allowing for multiple interpretations. For example, with respect
to possessives, one could distinguish between alienable and inalienable
possession, further subdivisions may be necessary on syntactic grounds (thus,
Heine and Kuteva 2002 distinguish three different syntactic types of possessive
constructions). The use of examples is thus a shortcut for such additional
functional characteristics. Other than that, it does not have any particular
theoretical status in my approach. In this respect, my approach is no different
from the use of examples by other authors, such as Haspelmath. This does not
mean, of course, that the choice of examples is completely unconstrained. One
minimal requirement is that the use of a particular marker should not be
idiomatic (i.e. highly lexically restricted). For this reason, an example like
This house belongs to John cited by Wälchli would
not count
as a felicitous example of the possessive use of the preposition, since it
expresses possession only in conjunction with a specific verb. (Such idiomatic
uses are a frequent source of exceptions/outliers on semantic maps, cf.
Wälchli’s 2010a discussion of the idiomatic uses of the source
preposition
de in the goal function in French).
3. What Is the Underlying Theory
of Similarity?
I cannot fully follow Wälchli when he writes that
“similarity is based on adjacency” in my approach. Rather,
similarity is reflected in adjacent ordering as well as through the use of
connecting lines, as is also standard in classical semantic maps. Indeed,
partial identity of adjacent/connected categories is frequently assumed in the
literature (explicitly or implicitly). This overlap is often captured in terms
of features (see Zwarts 2010), or, more generally, in terms of some shared
semantic components (as in Wierzbicka’s chain model of polysemy; e.g.
Wierzbicka 1980). I do not think that further decomposition of functions would
disturb the map, or that “if adjacency is indispensable for defining
similarity, this would mean that the degree of resolution cannot be
altered” (Wälchli 2010b). If a certain function is decomposed further
(e.g. Experiencer into Cognizer, Perceiver, etc.), its sub-varieties share more
semantic components with each other than with any other function of the same
granularity. If, for example, on a coarse-grained map of syntactic functions,
Agent is placed between Experiencer (both share the sentience feature) and
Instrument (both are instigating entities), the overall configuration should not
change if the roles are decomposed. In some versions of the (classical) semantic
map approach, this is explicitly represented by permitting inclusion relations
between more general vs. more specific functions on the map. (see van der Auwera
and Plungian 1998). Thus, “zooming in” on a particular domain does
not change the overall configuration of the semantic map.
Further, Wälchli challenges those approaches to semantic maps which
assume (like I do) that semantic similarity involves partial identity. The
extent to which such approaches succeed in identifying shared semantic
components should be judged on a case-by-case basis; yet I think it raises
interesting questions and stimulates semantic analyses to find a common
denominator behind different uses of a polyfunctional item. It is less clear to
me what the alternative research program of ‘similarity semantics’
as proposed by Wälchli is. It seems to me that it is content with a
statement of different degrees of similarity between particular uses, and stops
at this point without posing further research questions. For that reason, even
though I find Wälchli’s approach intriguing, I have certain
reservations about regarding ‘similarity semantics’ at this stage
(whatever its philosophical merits) as a serious competitor to the first
approach.
In his otherwise very sympathetic commentary, Heiko Narrog
rightfully draws attention to the fact that distinguishability effects differ in
some important respects from other interfering factors discussed in my paper. I
agree that distinguishability has a special status as a competing motivation; it
also stands out as another general functional factor in interaction with
semantic similarity, while most other interfering factors are structural, at
least in part. As I showed in my paper, distinguishability can induce two kinds
of effects. On the one hand, it can yield polysemies reflecting
“spurious” semantic connections. This seems to be more common in
minimal/highly restricted systems (paradigms). A classical example would be
‘morphological reversals’ or ‘polarity’ phenomena
(Baerman 2007), where a morphological opposition seems to reverse its function
across environments (e.g. the same marker is used for plural of feminine nouns
and for the singular of masculines). On the other hand, distinguishability can
also inhibit certain polysemies, thus masking a semantic connection (see section
4 of my paper for exemplification). The latter effect seems to be more common
and, as I argue in my paper, can explain why certain long-range polysemies do
not exist. Indeed, it might be advisable, as also suggested by Narrog, to
introduce special conventions for representing the effects of distinguishability
(both “spurious connections” as well as “blocking
effects”) graphically on the map.
References
Baerman, Matthew. 2007. Morphological reversals. Journal of
Linguistics
43/1.33-51. doi:10.1017/s0022226706004440
Haspelmath, Martin. 2007. Pre-established categories don't exist:
Consequences for language description and typology. Linguistic Typology
11/1.119-132. doi:10.1515/lingty.2007.011
Heine, Bernd and Tania Kuteva. 2002. World lexicon of
grammaticalization. Cambridge: Cambridge University Press.
Malchukov, Andrej L. 2010. Analyzing semantic maps: A
multifactorial approach. Linguistic Discovery, this issue. doi:10.1349/ps1.1537-0852.a.350
Narrog, Heiko. 2010. Optimizing classical maps. Comment on
Malchukov 2010. Linguistic Discovery, this issue. doi:10.1349/ps1.1537-0852.a.372
van der Auwera, Johan and V.A. Plungian. 1998. Modality’s
semantic map. Linguistic Typology 2/1.125-139. doi:10.1515/lity.1998.2.1.79
Wierzbicka, Anna. 1980. The case for surface case. Ann Arbor:
Karoma.
Wälchli, Bernhard. 2010a. Similarity semantics and building
probabilistic semantic maps from parallel texts. Linguistic Discovery, this
issue. doi:10.1349/ps1.1537-0852.a.356
-----. 2010b. Three questions about analyzing
semantic maps. Comment on Malchukov 2010. Linguistic Discovery, this
issue. doi:http://dx.doi.org/10.1349/ps1.1537-0852.a.373
Zwarts, Joost. 2010. Semantic map geometry: Two approaches.
Linguistic Discovery, this issue. doi:10.1349/ps1.1537-0852.a.357
Author’s contact information:
Andrej L. Malchukov
Department of Linguistics
Max Planck Institute for Evolutionary Anthropology
Deutscher Platz 6
04103 Leipzig
andrej_malchukov@eva.mpg.de
[1]
Thus Wälchli
(2010a) excludes from consideration local case markers related to (derived from)
verbs.
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