(10)
|
Darma (Willis 2011: 118)
|
|
|
a.
|
hã
|
mala
|
çya-lan ɟu,
|
ɟo
|
nini,
|
ʔa
|
dulaŋ
|
ʈʰo-dan
|
|
|
then
|
garland
|
put.on-cvb
|
after
|
hm
|
hm
|
cake
|
toss.ritually-1pl.npt
|
|
|
‘Then after putting on the garland, um, (we)
ritually toss the cake’ (Haircutting Ceremony)
|
|
|
b.
|
tsɛmmɛ
|
su!
|
|
|
girl
|
agt
|
|
|
‘The girls (do it)!’ (Hair-cutting Ceremony)
|
|
|
|
|
|
|
|
|
|
|
|
Related to this contrasting
function is the use of PMA marking to encode a shift in perspective. Lidz
(2011: 56) observes that the presence of agentive case marking in Yongning Na
correlates with a change in viewpoint from one participant to another and
suggests that the marking is contributing to a foregrounding function in
discourse. She compares this foregrounding function to a similar use of
agentive marking reported in Khumi (Peterson 2011), which also uses a case
marker for foregrounding participants in narrative discourse, particularly when
they are behaving contrary to expectations or notions of volitionality.
3.3 Encoding extraordinary, willful or unexpected
behavior
Unusual turns of events
are often signaled in TB languages by the use of PMA marking. Willis (2011:
114) describes how a core argument of ‘sit, live’ occurs with agentive marking
in a narrative text because the NP referent, a local king, is hiding
underground instead of living in his palace. This represents an unexpected and
marked situation, and its peculiarity is brought into focus by the speaker’s
use of the agentive marker su.
(11)
|
Darma (Willis 2011: 114)
|
|
|
…cet
|
ru,
|
ʔu
|
su,
|
ɟo
nini,
|
ki
|
raɟa,
|
ɟo
nini,
|
ʔu
|
da,
|
raɟa
|
|
place.name
|
loc
|
3sg
|
agt
|
hm
|
that.ln
|
king.ln
|
hm
|
3sg
|
cont
|
king.ln
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
da
|
andergrawnd
|
ru
|
çyuŋ-çyɛ-n
|
le-ɟu.
|
|
|
|
|
cont
|
underground.ln
|
loc
|
live-mid-nmlz
|
aux.ex-pst
|
|
|
|
‘…in Cet, he, that is,
that the king, um he, the king was living underground.’
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
One of the functions of
PMA marking in Mongsen Ao is to encode increased agency. As in Darma, the verb li ‘stay,
live’ does not normally require an agentive-marked core argument, but in the
following textual example a woman threatens to desert her husband if he does
not acquiesce to her demand for him to kill her stepson. This represents a
pragmatically-marked situation, and the narrator strongly encodes the
stepmother’s intent by assigning PMA marking to the 1st person
pronoun in the apodosis.
(12)
|
Mongsen Ao (Coupe 2017:
291)
|
|
nàŋ
nə̄ ānū ī mə̀tə̄psə̀ttʃūkpàlā, nì nə̄ nə̄thə̄n mə̀lījùʔ, tə̀ sā, ɹ̥āpītsə̄ɹ tʃū
nə̄.
|
|
nàŋ
|
nə̄
|
ānū
|
ī
|
mə̀-tə̄psə̀t-tʃūk-pàlā
|
nì
|
nə̄
|
nə̄-thə̄n
|
|
2sg
|
agt
|
nrl-child
|
prox
|
neg-kill-pfv-cond
|
1sg
|
agt
|
2sg.poss/obl-com
|
|
|
|
mə̀-lī-ì-ùʔ
|
tə̀
|
sā-Ø
|
ɹ̥āpītsə̄ɹ
|
tʃū
|
nə̄
|
|
|
neg-stay-irr-decl
|
thus
|
say-pst
|
stepmother
|
agt
|
dist
|
|
‘“If you do not kill
this child, I will not stay with you”, said the stepmother.’
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Similarly, the Mongsen
Ao verb tʃàʔ ‘consume’ does not
normally require an actor argument to be assigned agentive case marking when
reporting on a typical, everyday event of eating. However, the following pair
of carefully elicited sentences demonstrates how the agentive marker nə̄ can be used to encode a willful actor that
is behaving with increased volitionality and intent. The context in which (13a)
applies is a default situation in which chickens are fed a handful of paddy and
the speaker reports on the event, whereas (13b)
reports on a pragmatically-marked situation. Chickens freely wander around Ao
villages and sometimes they opportunistically pilfer unguarded paddy, which is
left exposed on mats to dry in the sun. One day a Mongsen Ao speaker was
informed that some chickens were raiding his drying paddy and was asked what
was happening, and (13b) was uttered in response as he chased the
raiding chickens away. There is a clear difference in meaning between the two
sentences, and this is created by the addition of the PMA marking in (13b).
The chickens learn from experience that villagers will try to beat them for
stealing the drying paddy, so it is plausible that their augmented agency is
encoded in such pragmatic contexts by the presence of the agentive marker.
(13)
|
Mongsen Ao (Coupe 2007:
157)
|
|
a.
|
ahən atʃak tʃàɹùʔ.
|
|
|
a-hən
|
a-tʃak
|
tʃàʔ-ə̀ɹ-ùʔ
|
|
|
nrl-chicken
|
nrl-paddy
|
consume-pres-decl
|
|
|
‘The chickens are eating
paddy.’ (elicited data)
|
|
|
b.
|
ahən nə atʃak tʃàɹùʔ.
|
|
|
a-hən
|
nə
|
a-tʃak
|
tʃàʔ-ə̀ɹ-ùʔ
|
|
|
nrl-chicken
|
agt
|
nrl-paddy
|
consume-pres-decl
|
|
|
‘The chickens are eating
paddy.’ (implying that they are stealing it)
|
|
|
|
|
|
|
|
According to Chelliah (2009:
387), extraordinary behavior is analogously signaled by agentive marking in
Meithei, as captured by the contrast in the following pair of sentences.
(14)
|
Meithei (Chelliah 2009:
387)
|
|
a.
|
tomba
|
chá
|
čá-í.
|
|
|
Tomba
|
meat
|
eat-nhyp
|
|
|
‘Tomba ate meat.’ (Tomba
is a non-vegetarian.)
|
|
|
b.
|
tomba-nə
|
chá
|
čá-í.
|
|
|
Tomba-agt
|
meat
|
eat-nhyp
|
|
|
‘Tomba ate meat.’ (A
noteworthy activity, not expected for this vegetarian.)
|
|
|
|
|
|
|
|
Many TB languages
freely permit the ellipsis of core arguments if they are recoverable from the
context. When an argument of a bivalent verb is elided, the presence or absence
of case marking on the remaining argument clarifies its semantic role,
especially if this cannot be correctly deduced from the context. This function
is demonstrated in the following pair of Kurtöp sentences.
(15)
|
Kurtöp (Hyslop 2010: 12)
|
|
a.
|
nyarop
|
zon
|
phang-zi
|
|
|
fisherman
|
two
|
feel.pity.for-nf
|
|
|
‘The two fishermen were pitied...’ (elicited data)
|
|
|
|
b.
|
nyarop
|
zon-gi
|
phang-zi
|
|
|
fisherman
|
two-agt
|
feel.pity.for-nf
|
|
|
‘The two fishermen felt pity (for the prince and princess) ...’
|
|
|
|
|
|
|
Lidz (2011: 58) notes
that agentive marking possibly plays a disambiguating role in some Yongning Na
sentences, in addition to highlighting agency. Without the agentive marking on mi³¹ zɤ¹³ in
(16), for example, the meaning could be
understood as ‘Again (he) went to teach the woman’.
(16)
|
Yongning Na (Lidz 2011:
58)
|
|
wɤ¹³
|
mi³¹ zɤ¹³
|
nɯ³³
|
tʰɯ³³-sɔ¹³
|
hɯ³³
|
|
again
|
woman
|
agt
|
dur-teach
|
go
|
|
‘Again, the woman went
to teach (him).’
|
3.5 PMA marking in causativized clauses
Just as the occurrence of
a single agentive-marked NP in a clause with a bivalent verb serves to indicate
an actor semantic role, so can the absence of case marking on an NP indicate an
undergoer semantic role. This function of core case marking is particularly
important for clarifying meaning in Mongsen Ao causativized clauses with elided
arguments. Causativization obligatorily triggers agentive marking on a causer
argument and either zero or dative marking on a causee argument;
this represents one of only two situations in which the disambiguating function
of agentive marking is consistent and mandatory. The referent of the
zero-marked 3rd person pronoun pa is
accordingly identified as a causee in (17a), whereas the
presence of agentive marking on wàzàʔ in the consecutive sentence of (17b)
establishes that NP as the causer argument.
(17)
|
Mongsen Ao (Coupe 2011b:
514)
|
|
a.
|
təɹ pa tsəpàʔ ku atsə mə̀tʃəməjùʔ.
|
|
|
tə̀-əɹ
|
pa
|
tsəpàʔ
|
ku
|
a-tsə
|
mə̀-tʃəm-iʔ-ı̀-ùʔ
|
|
|
thus-seq
|
3sg
|
pond
|
loc
|
nrl-water
|
neg-drink-caus-irr-decl
|
|
|
‘And, [they] would not
let her drink at the pond.’
|
|
|
|
b.
|
təɹ wàzàʔ nə tsəpàʔ ku
atsə mə̀tʃəmilà.
|
[mə̀-tʃəm-iʔ-là]
|
|
|
tə̀-ə̄ɹ
|
wàzàʔ
|
nə̄
|
tsə̄pàʔ
|
kū
|
ā-tsə̄
|
mə̀-tʃə̄m-īʔ-là
|
|
|
thus-seq
|
bird
|
agt
|
pond
|
loc
|
nrl-water
|
neg-drink-caus-neg.pst
|
|
|
‘And, the birds didn’t
let [her] drink at the pond.’
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Obligatory
disambiguating agentive marking in causativized clauses could plausibly provide
a pathway to the development of consistent marking of all A arguments if it is generalized
to non-causativized clauses, possibly resulting in the grammaticalization of a
paradigmatic ergative-absolutive alignment pattern (cf. the related discussion
of generalization in Section 6).
3.6 Characterizing
habitual activity
Some TB languages use
agentive marking in generic statements not to express meanings associated with
any of the situations described above in Sections 3.1-3.4, but to encode
instinctive or habitual behaviors. Such usages seem far removed from the
functions of PMA marking seen in preceding examples, or from the expression of
increased agency, personal choice or unexpected behavior often associated with
this type of case marking. Chelliah (2009: 387) accounts for the use of
agentive marking for this purpose in Meithei by proposing that agents
case-marked by the agentive marker -nə can
be understood as performing an activity that characterizes the class of
referent or the force of tradition, e.g.
(18)
|
Meithei (Chelliah 2009:
391)
|
|
a.
|
hindu-síŋ-nә
|
lukun-si
|
tháŋ-í
|
|
|
Hindu-pl-agt
|
sacred.thread-prox
|
wear-nhyp
|
|
|
‘Hindus wear the sacred
thread.
|
|
|
|
b.
|
učék-siŋ-nә
|
sul
|
atiya-tә
|
pay-í.
|
|
|
bird-pl-agt
|
air
|
sky-loc
|
fly-nhyp
|
|
|
‘Birds fly in the open
air.’
|
|
|
|
|
|
|
|
|
Coupe (2011b: 499)
compares a very similar meaning encoded by agentive marking in generic
statements in Mongsen Ao. Possibly the agentive marker encodes a type of
referentiality in this instance of use. If so, it somewhat mirrors the use of
dative marking on O arguments in some languages to encode increased
referentiality, as in Spanish and Hindi. The difference between the two
sentences of (19a-b) below is that example (19a)
without the agentive marking reports an activity in progress (which was uttered
in response to the question “What are you doing?”), whereas the elicited
example of (19b) with agentive marking on the 1st
person argument expresses a characterizing meaning consistent with the
preceding Meithei sentences (cf. also Lestrade and de Hoop 2016).
(19)
|
Mongsen Ao (Coupe 2011b:
499)
|
|
a.
|
nì
asəŋ səɹə̀
|
|
|
nì
|
a-səŋ
|
sə-ə̀ɹ
|
|
|
1sg
|
nrl-wood
|
chop-pres
|
|
|
‘I’m chopping wood.’
|
|
|
|
b.
|
nì
asəŋ səɹə̀
|
|
|
nì
|
nə
|
a-səŋ
|
sə-ə̀ɹ
|
|
|
1sg
|
agt
|
nrl-wood
|
chop-pres
|
|
|
‘I chop wood.’ (i.e.
habitually, as an occupation)
|
|
|
|
|
|
|
|
Having illustrated the
wide variety of non-syntactically determined situations in which PMA marking appears
in TB languages, our attention will now turn to a consideration of the
diachronic sources of core relational morphology – how spatial case marking
first develops from relational nouns expressing locations, and how this is
metaphorically extended to encoding even more abstract uses in grammar. This
can be most conveniently demonstrated with reference to the development of
agentive case markers in Mongsen Ao and Tibetan.
Grammaticalization studies consistently demonstrate pathways of
development from more concrete concepts to more abstract concepts in grammar. This
trajectory has been noted by numerous authors who have sought to explain how
complexity develops in grammar (e.g. Givón 1971, 1979, 2009; Heine et al. 1991; Heine & Kuteva 2002,
2007; Dahl 2008, among others). In TB languages as well as in many other
head-final languages of the world, nouns are typically found to grammaticalize
as case-marking postpositions from appositional or genitival constructions that
initially encode concrete spatial meanings, such as location, source and goal
(DeLancey 1984: 62; Aristar 1991; LaPolla 1995: 214, 2004; and Coupe 2011b:
506).
Once a spatial noun is reinterpreted as a postposition encoding an
oblique relational meaning, it may then be used in an innovative way for
encoding even more abstract functions of grammar, such as for marking a core
grammatical case relation. Grammaticalized relational morphology is
additionally often the target of further cycles of reanalysis that develop yet
more syntactic uses. For example, space > time grammaticalizations are a
particularly common pathway for the development of reanalyzed functions of case
marking morphology in many of the world’s languages – see Genetti 1986, 1991 and
Coupe 2007, 2017 for accounts of how case markers become reinterpreted as
non-finite converbal suffixes encoding a range of temporal and/or adverbial
presuppositions in TB and other head-final languages of South Asia.
Given the ubiquity
of a syncretic agentive/instrumental form na~nə in all
but one language of the Ao group of central Nagaland (viz, Mongsen Ao, Lotha,
Sangtam and Yimchungrü), it can be reconstructed to the level of Proto-Ao as *na (Coupe 2011a: 32). The Ao dialects go one step
further and are universally unique in sharing a case syncretism involving not
only the above-mentioned agentive and instrumental cases, but also an allative
case. The following Mongsen Ao proverb demonstrates these three case relations
in the one clause:
(20)
|
Mongsen Ao (Coupe 2007: 172)
|
|
aji nə tuɹ nə athùtʃən nə anətpən wa mə̀tə̀m.
|
|
ā-jī
|
nə̄
|
tūɹ
|
nə̄
|
āthùʔ-tʃə̄n
|
nə̄
|
ā-nə̄t-pə̄n
|
wā
|
mə̀tə̀m
|
|
nrl-dog
|
agt
|
gpn
|
inst
|
vomit-lnmlz
|
all
|
nrl-two-ord
|
go
|
like
|
|
‘Like a dog going back to its vomit by itself for
a second time.’
|
|
(= to eat one’s words; to reject something and
then want it later)
|
The likely lexical
source of this relational morpheme is Proto-Tibeto-Burman *ʔ‑nam ‘side/rib’, as reconstructed by Matisoff 2003 for
Proto-Lolo-Burmese. A cognate form tə-na occurs in the Chungli dialect of Ao, defined
by Clark (1911: 626) as meaning ‘side at the waist where there are no ribs’. The noun
‘side’ is also a known lexical target for the grammaticalization of locatives
in Chinese and some French-based pidgins and creoles (Heine & Kuteva 2002:
272). Similarly, Beames (2012[1875]: 257) proposed that the lexical origin of
the Hindi dative marker ko is the locative declension of Sanskrit kákṣa-
‘armpit’. Reinöhl (2016: 58–59) suggests that this lexical meaning was metaphorically extended
first to ‘side of body, flank’, then to the marking of goals and recipients,
and finally to the marking of human and definite patients in a further
metaphorical extension of function.
The Proto-Ao form *na plausibly grammaticalized as a type of local case
marker from the relational head of a compound noun. This is consistent with
LaPolla’s (1995) observations concerning the diachronic origins of TB
case-marking systems, except for the fact that an
allative/agentive/instrumental isomorphism is an unattested syncretism in his
survey; neither was it encountered in the study of Bodic case marking
syncretisms by Noonan (2009). It is much more typical for the grammaticalized
marker of a goal to be metaphorically extended to marking a core O argument, as
demonstrated by the Hindi dative/accusative marker ko. However, at the initial stage of
grammaticalization, Proto-Ao *na presumably functioned simply as a semantically
unspecified marker of a local case relation, as suggested by the multiple case
roles encoded by a syncretic form in the synchronic grammar of the Mongsen
dialect (e.g. [20]), so theoretically any oblique case role could have been
metaphorically extended to a core marking function (cf. Lestrade 2016b for a
discussion of unspecified local relations). Because agents and instruments are
in some sense both effectors of events and activities, logically it must have
been the instrumental meaning of *na that was
the target for the grammaticalization of the agentive marking function.
A similar development is suggested by the isomorphic form of the
agentive/instrumental marker in Tibetan. LaPolla (1995: 191) reconstructs a
syncretic agentive/instrumental marker -s(V) in sub-groups of the Bodish branch of
TB and observes that this morpheme is also partially isomorphic with the
ablative marker (in common with Mongsen Ao, whose ablative form is phinə). The probable lexical source is an earlier Proto-Tibetan relational
noun *-sa ‘place’, which is also used to derive nominalizations such as khuŋ ‘hole, pit, cavity’, khuŋ-sa ‘hole place’ > khuŋs ‘mine’; khoŋ ‘the inside’, *khoŋ-sa ‘inside place’ > khongs ‘middle, midst’; and ŋo ‘face’, ŋo-sa ‘face-place’ > ŋos ‘side, direction, surface’ (Beyer 1992: 118).
The agentive marker -s of modern Tibetan is very similar in form
to the grammaticalized relict of ‘place’ in Classical Tibetan, so this
constitutes another instance of the relational noun > oblique postposition
> core case marker development that is attested in many head-final languages.
(21)
|
kho-s
|
bu.mo
|
snying.rje.po
|
de-la
|
btlas-song
|
|
|
he-agt
|
girl
|
nice
|
this-obl
|
look-aor+evid
|
|
|
‘He looked at the nice girl.’ (Tournadre 1991:
94)
|
Once a lexical item has grammaticalized as a postposition, its new grammatical
roles are open to a range of relational interpretations. This accounts for the
frequently observed case syncretism in TB languages (e.g. Noonan 2009, Coupe
2011a), as well as in many other language families of the world – isomorphic
ergative/instrumental and ergative/ablative markers are reported to be
especially common (LaPolla 1995, 2004. Since only one argument may need to be
grammatically marked for the disambiguation of meaning, a language has the
option of overtly marking either the A argument or the O argument of a bivalent clause, and this choice potentially
has ramifications for whether a language may eventually grammaticalize a
paradigmatic nominative-accusative or ergative-absolutive alignment pattern.
Both are possible eventual outcomes of the grammaticalization of core argument
marking.
The Apatani examples of (22) are illustrative of the disambiguating O
marking pattern. In this language, dative case is extended to marking an O
argument to disambiguate semantic roles in bivalent clauses. The innovative
dative marking is only obligatory when the referents of both core arguments are
possible instigators of an event. For this reason, LaPolla (1992, 1994) refers
to the pattern as ‘anti-ergative’ marking, as it distinguishes an NP argument
as not being in A function. This term
was later replaced by ‘anti-agentive’ to make it more widely applicable to TB
languages. The current fashion is to refer to the pattern as ‘differential
object marking’ (DOM) in the typological literature, principally after Bossong
1985.
(22)
|
Apatani (Abraham 1985: 38-40)
|
|
a.
|
ŋɨ-ka
|
anɨ
|
tade
|
mi
|
yo
|
bi-bɨ-ne
|
|
|
1poss-gen
|
mother
|
pers.name
|
dat
|
meat
|
give-evid-nprox
|
|
|
‘My mother gave meat to Tade’
|
|
|
|
b.
|
sɨhɨnɨ
|
mó
|
mi
|
alitu-bɨ-ne
|
|
|
cow
|
3sg
|
dat
|
kick-evid-nprox
|
|
|
‘The cow kicked him’
|
|
|
|
c.
|
mó
|
sɨhɨnɨ
|
pa-bɨ-ne
|
|
|
3sg
|
cow
|
kill-evid-nprox
|
|
|
‘He killed the cow.’
|
|
|
|
|
|
|
|
|
|
|
|
|
If semantic roles can be assigned unambiguously because of the semantic
nature of the referents, and the A argument also precedes the O argument, then no
marking appears on a core argument. But if
the preverbal constituent order is reversed, so that the O argument precedes
the A argument, then dative marking on the clause-initial undergoer argument
becomes obligatory to override assumptions that the most topical NP represents
the A argument. Example (22a) demonstrates the expected use of dative case to
mark the recipient NP of a three-place predicate, and example (22b) shows its
innovated use as a disambiguating marker on the O argument in a bivalent clause.
This is motivated by the fact that the agent of ‘kick’ could be either of the
referents, as both are animate. Conversely, (22c) demonstrates that the dative
marking does not occur on the O argument when referents are acting in ways
consistent with expected behavior.
The variable use of dative case marking on a core argument is widely
reported across many languages, including Bantu and the Romance and
Indo-Iranian branches of Indo-European (e.g. Hopper & Thompson [1980: 256];
Bossong 1991, inter alia). Since
dative marking on an O argument can also be exploited for the discrimination of
semantic roles – as demonstrated by the Apatani data – in many respects it
mirrors the disambiguating marking functions of PMA marking outlined in Section
3.
To summarize our findings thus far, it has been shown that
non-paradigmatic PMA marking is rather more widespread in TB languages than was
previously appreciated. Our fundamental conclusion is that the purpose of the
agentive marking is disambiguation, which develops from the innovative use of a
spatial case marker in a metaphorically extended core function.
Diachronic evidence from Tibetan and Ao suggests that a lexical noun in
an appositional or genitival construction first becomes grammaticalized as a
local case marker/postposition, and then is subsequently pressed into a more
abstract role as a disambiguating core case marker, but only when non-canonical
constituent orders or possible confusions over the assignment of semantic roles
may result in misinterpretations of meaning. Virtually all of the other uses of
agentive marking discussed in Section 3 can be attributed to further extensions
of this basic disambiguating function. The presence of agentive marking in
these languages is convincingly demonstrated to be unrelated to syntactic
valency, which accounts for why it is found on both A and S arguments of
bivalent and monovalent clauses under pragmatically predictable conditions.
The question now is whether these findings can be
generalized, and whether other case-marking systems can be shown to develop in
similar ways. The next sections will discuss a
series of computer simulations of the emergence of case marking leading to
similar results indeed. These computer simulations are run using the R package MoLE, for
modelling language evolution, which is available from CRAN
(http://www.cran.r-project.org/).
Given the
methodological break, it is probably best to start this second part of the
paper with a few disclaimers and general remarks on using computer simulations
in linguistics. The main
goal of computational models of language evolution is to show how aspects of language may
develop as a result of more general principles (for
recent overviews, see e.g. Smith
2014, Gong & Shuai 2013, Jäger et al. 2009, Cangelosi & Parisi 2001). Note that this can only be used as a proof of concept: a positive
result does not mean that this is the way things must have gone, it only shows
the feasibility of certain phenomena to emerge from the assumptions implemented
in the model. But the more linguistically and typologically informed the model,
the more interesting the results, of course. Unfortunately, evolutionary models
mostly are fairly abstract. In MoLE, for example, agents lack spatial concepts
and hence case markers cannot be derived from spatial notions (cf. Section 4). Also,
at least in the present study, there is no interaction between the use of case
marking and word order. Thus, whereas in Qiang the less agent-like participant
is marked if it qualifies for the more agent-like role in principle and precedes the actual agent in linear
order (cf. example [4]), only the former motivation plays a role in the model
(but see Lestrade to appear).
Finally, the present simulation is restricted to the marking and disambiguation
of generalized semantic
roles. Note however that the encoding of other meaning aspects can be
understood in the same vein: speakers check whether all meaning aspects of a
proposition are likely to be understood by their hearers. If they think some
relevant ingredient will not come across, whether this concerns a role or
something like intentionality, this needs to be encoded explicitly.
On the basis of the previous
section, one may be led to think that languages simply choose between marking
the A or O argument if an utterance needs elaboration, the options being
equivalent for disambiguation purposes. As will be shown in the simulations,
however, things are a bit more complex: The available markers to choose from
first have to be developed themselves, and their availability obviously
constrains the options. In the beginning of the simulations, as for natural
language, arguably, there are no case markers available. Instead, lexical
ad-hoc solutions are used to resolve imminent communicative failure. For example in (23), the noun pokynut ‘teacher’ is used to mark dutypog ‘boy’ for its teaching role. Note that these glosses are for convenience only, as meaning in the
model is completely abstract (cf. Section 7.1).
(23)
|
dutypog
|
pokynut
|
nisagufy
|
rapykume
|
|
boy
|
teacher
|
man
|
teaches.V
|
|
‘The boy is teaching the man.’
|
In the model, the eventual
development of case markers involves the initial recruitment and subsequent
grammaticalization of lexical items such as pokynut in (23). These are words with a
very specific referential meaning, which are used in combination with small
sets of verbs only (viz. those with similar role specifications; e.g. instruct for the current example). Only
later some of these words may become more general in meaning and shorter in
form in the process of grammaticalization. Importantly, recruitment itself
depends on more general solution strategies: If no grammatically determined
solution method has been arrived at yet, which argument should be marked (using
ad-hoc lexical expressions): the worst performer, the one for which the
simplest solution is available, or just either of them? These different options
will be entertained in Section 7 below. Before we can discuss the results of
these strategies, however, a brief introduction to the model will be necessary.
The general idea and architecture of the model have previously been
introduced (Lestrade 2015a/b, 2016a, to appear), and this section will largely
be an (updated) recapitulation of that. Readers already familiar with the model
may wish to skip this section, picking up at Section 7.2, which introduces the solutionMethod parameter that is newly
developed for the purpose of this paper.
In the model, agents talk, procreate halfway
through their lives, and die after 2000 utterances. They consist of a lexicon,
distinguishing between object and action words, a usage history that keeps
track of all contexts in which words have been used (cf. Bybee 2010), and a
“language-ready” brain, which basically means that the agents have a desire for
communicative success and are capable of joint attention (Tomasello 2003, Arbib
2015). In addition, during conversation, agents build up a common ground
consisting of the set of recently used referential expressions.
The general conversation procedure is given in
Figure 1. Two agents are selected for conversation and find themselves in a
situation that consists of a set of randomly created events (to be qualified
below). One of the agents wants to refer to one of these events, the target
event, for which it formulates an utterance (roughly using the
incremental and modular procedure described in Bock & Levelt 1994). If the
speaker agent thinks some part of the intended meaning is insufficiently clear,
it will elaborate to make it explicit (Steels 2003, Blutner 2007, Zeevat 2007,
de Swart 2007, Lestrade 2010). Initially this involves the use of lexical
ad-hoc marking through simple lexical apposition for the lack of conventional
solutions, as shown in (23) above; once case marking develops, however, this
will be used instead. Next, the hearer has to analyze the utterance by
identifying the words and their functions, determine the intended meaning, and
point out which event in the situation it thinks the speaker referred to. If
correct, the common ground, usage history and lexicon will be updated, and the
conversation will continue. If they fail, the conversation will continue
without updating.
Figure 1: Conversation procedure
In what follows we will go through the different
steps and ingredients in more detail. We will start with the lexicon, which, as
in other recent proposals about the cognitive architecture of language, is put
center stage (Vosse & Kempen 2000, Kempen 2014; Jackendoff 2002, 2011;
Culicover & Jackendoff 2005). Since agents live in a virtual world, their
meaning representations are rather different from ours. Fortunately, it seems
possible to implement this in a relatively valid way nevertheless. According to
Wierzbicka (1996), natural-language concepts can be decomposed into meaning
primitives such as concrete, human, male,
etc. (cf. also Katz & Fodor 1963 and Guiraud 1968). Similarly, in a way,
Gärdenfors (2000) argues that concepts are sets of values on different meaning
dimensions. Thus, we can think of a cat as something that is time-stable,
concrete, alive, four-legged, tailed, etc. Note that whereas the initial
meaning dimensions in such characterizations are very general and bisect the
world (e.g. time-stability), eventually meaning dimensions become more and more
specific in order to single out a concept (e.g. having a tail). Abstracting
away from the quality of the dimensions that organize our mental lexicon, the
object lexicon of the agents is modeled as a list of randomly generated forms
with values on nine numerical meaning dimensions (their vector representation). An example is given in (24). Following the
observation just made, the dimensions make an increasing number of distinctions
(with values between zero and one). These dimensions may be taken to represent
whatever properties are (grammatically) relevant for the linguistic behavior of
words in natural language, but the model does not commit to any such specific
interpretation per se. Action
words can be similarly specified (their dimensions representing different
semantic features), with the eventual addition of one (for one-place
predicates) or two predicate roles (for two-place predicates), which are
represented using vectors as well, cf. (25). In the remainder, object words are
sometimes called nouns and action
words verbs for the sake of
convenience, which should be understood in a theory-neutral way.
(24)
|
Representation of nouns
|
|
|
dotyjytit
|
1 1 0 1 0 0.000 0.250 0.25 0.00
|
|
|
|
|
(25)
|
Representation
of verbs
|
|
|
tomorawog
|
1 0 0 1 1 0.375
0.875 0.000 1.000
|
|
role 1
|
1 1 1 1 1
0.375 0.875 0.750 0.250
|
|
role 2
|
0 0 0 0 0
0.500 0.50 0.875 1.000
|
|
|
|
|
The meaning dimensions of nouns and verb roles
correspond to one another in the model. That is, the first predicate-role dimension
concerns the same property as the first noun dimension. These correspondences
are used to determine the role qualifications of the nouns (or typing scores, after Aristar 1997). The
more the vector of a noun resembles that of a verb role, the more it qualifies
for it.
In the model, higher
values, i.e. those closer to 1, are considered more prominent (for nouns) or
agent-like (for roles) than lower values. Note that a correspondence is thus
assumed between referential prominence and agentivity. That is, being prominent means being a typical A, and vice versa, and
similarly for non-prominent Os.
As exemplified by the verb
representation in (25) already, if a verb has two role vectors, one of them
contains higher values than the other on average. This is meant to reflect the
semantic role distribution in natural languages, in which the predicate roles
of two-place verbs generally can be distinguished in terms of agentivity, one
role being more agent-like than the other (Dowty 1991, Van Valin 1999, Yip et
al. 1987).
Just like meaning representations, events consist
of sets of vectors, one containing the referential properties of the action,
one for the more agent-like event participant, corresponding to the A argument,
and one for the less active one, which will be expressed as the O. Events are
generated randomly, as said above, but not entirely at random. In principle, events are made up of actions and objects
that could be expected to occur together, subject to a bit of noise. Nouns in
the common ground are more likely to figure in the events, and the distribution
of prominence values over A and O roles follows that of natural-language (as
established by Dahl 2000). The distribution for two-participant events is given
in Table 1. Roughly, and as well-known, As are mostly
prominent (speech-act participants or animate), Os mostly non-prominent
(inanimate).
role
|
prominent
|
non-prominent
|
A
|
93%
|
7%
|
O
|
16%
|
84%
|
Table 1: Animacy and (generalized)
semantic role (after Dahl 2000)
When developing an
utterance, the agents have to select referential items on the basis of the
vector match between their meaning representations and the actual referents to
be described. In principle, the form of the concept that best describes a
referent will be selected to describe it. In addition to semantic match,
however, frequency and economy considerations play a role: Frequently and
recently used (“activated”) words are preferred, as are semantically and
formally light expressions (see below for how words may become “light” as a
result of grammaticalization). For each meaning, word candidates are ranked
according to their activation and vector match, and the first word found to be sufficiently distinctive is selected for
expression.
Whether a word is
sufficiently distinctive depends on the number of distractor events and objects
in the contextual situation. If there are many events ongoing, it is generally
necessary to be more specific to prevent referential ambiguity (e.g., if
there’s more than one object present, thing
does not distinguish between them). Once the referential expressions have
been selected, the initial proposition is ready (cf. step 1 in Figure 1).
Although not entirely uncontroversial, it seems
that human communication is bidirectional, speakers taking into account their
hearers in order to be understood (as was already assumed in the previous step,
in fact). In many theoretical and computational models, this involves speakers
pretending to be hearers to check if they themselves would get the right
meaning (cf. Grice 1975, Levelt 1983, Hurford 1989, Steels 2003, Blutner et al.
2006, de Swart 2007, Zeevat 2007, Lestrade 2010). Economy and predictability
are generally considered two important factors in this process. Speakers try to
use as economic an utterance as possible (i.e. costing little pronunciation
effort). Only if this leads to the wrong result, the utterance should be made
more explicit (cf. Grice 1975). As discussed above already, the meaning
dimensions of nouns and verb roles correspond to one another in the model. That
is, the first predicate-role dimension concerns the same property as the first
noun dimension. By comparing these vectors, the degree to which an argument
qualifies for its role can be determined. Whenever a participant’s typing score
for its intended predicate role is significantly higher than that of the other
participant and that for the other role (i.e. under the reverse distribution of
roles), an agent can simply combine the words that refer to the event and event
participants. The argument structure then follows from their semantics (i.e.,
even in the absence of functional word order, we know who’s doing what in book man read). But if the intended role
filler does not qualify better than the other argument and hence the argument
structure does not follow automatically (cf. man boy see), something extra needs to be
done. One solution is to make the role of one of the participants explicit by
naming it using another word that describes this role best (cf. the notion of differential case marking, cf. e.g. Bossong 1985, Aissen 2003, de Hoop and de Swart 2008;
another solution, which is not entertained in the present experiment, is using
word order). Once the role distribution is checked and, if necessary, made
explicit through additional marking, the (elaborated) proposition can be
produced (steps 2 and 3; cf. Section 7.2).
The hearer now has to decompose the utterance,
distinguishing the referential expressions from the (ad hoc) role markers.
First, it has to be determined what the verb is in the utterance. This is done
by first determining which verb lexeme in the lexicon each word in the
utterance could correspond to, and next determining which of the actions in the
ongoing events are best described by the identified lexemes. The word with the
best-combined form and action match is considered the verb. Depending on the
type of verb (i.e. one- or two-place) and the number of remaining words,
different analyses might be possible. If, for example, the first word has been
identified as a two-place verb and three words remain, either the third word
could be a role marker of the second, or the fourth could be the role marker of
the third (assuming that role markers are adjacent and follow their hosts; cf.
Givón’s 1995:188 proximity-relevance
constraint). Alternatively, one or more words could be left unanalyzed, which
is penalized but may eventually lead to the preferred interpretation
nevertheless. All grouping possibilities are entertained and interpreted by
looking up and combining the semantics of the ingredients (Steps 4 and 5).
Next, for each interpretation it is determined how
well it describes each of the ongoing events. The interpretation with the best
match is considered the intended meaning and the corresponding event is
considered the target event (following the setup of Steels 1997). If the hearer
correctly identifies the target event, then the lexicon, common ground, and
usage history are updated (Step 7). If not, nothing happens. Finally, agents
may switch speech roles and continue their conversation (Step 8) or stop
talking, after which two new agents are selected.
Initially, all words are fully specified on all
meaning dimensions and have a word length of between 8 and 10 characters (as in
examples [24] and [25] above). Over time, however, words can change. For this,
a number of grammaticalization principles are implemented (Heine & Kuteva
2007), most importantly erosion and desemanticization. Words can be
‘‘pronounced’’ sloppily if they are frequent or predictable (cf. Jurafsky et
al. 2001 and Balota & Chumbley 1985). In the model, sloppy pronunciation is
instantiated simply by deleting the final character of a word. This does not
lead to a change of lexical representation for the agent using the form, but if
new generations of speakers attest only the shorter variant, they may set their
lexical representation accordingly, because of which a form may erode (Nettle
1999). If words become too short to stand on their own, they are fused with
their host, first as a clitic, and eventually as a suffix (Bybee 1985). In the
model, this concerns those words for which the total production effort (i.e.
the number of characters) has fallen below the suffix threshold of 6. Note
that, in principle, the difference between bound and non-bound marking (or
between suffixes and postpositions) is thus understood as one of “phonological”
degree only. However, for erosion to get this far, something has to happen on
the meaning side too.
Frequent words are likely to desemanticize. At
first, they may extend their meaning range incidentally (if the context does
not require a more specific description or in the absence of a better
expression). Eventually, such an extension may become a standard part of a
word’s meaning, as a result of which it becomes more general. In the model,
desemanticization involves the progressive removal of the meaning dimensions of
a word. Shortly before they procreate, agents consider the variation in their
usage history and may decide that certain meaning dimensions should either be
changed or be removed from the meaning representation of a word (Bybee 2010). A
meaning dimension of a word is changed into another value if this latter value
is found significantly more representative for the meanings for which this word
has been used. Deletion takes place if some meaning dimension is found to be
unrepresentative or inconsistent with the uses of the word, but there is no
dominant value on that dimension among the uses. In addition, certain frequency
thresholds need to have been reached: for a first dimension to be removed, a
word has to be combined with 2% of the relevant predicates. This proportion
grows exponentially to 40% for the last dimension to be removed. The less
dimensions specified, the more general or abstract the meaning, and the more
usage possibilities. Together with the attenuated phonological form, a
generalized meaning constitutes what could be understood as the model
equivalent of a case marker: a maximally short form with a maximally general
meaning (Lestrade 2010).
In
addition to erosion and desemanticization, a third grammaticalization principle
is implemented, viz. generalization. Agents
not only keep track of the referential meanings of words, they also do this for
the type of constructions they have used. Thus, a score is kept for how often
As and Os were marked for their role. More specifically, agents keep track of
the meaning values that are involved in this. For example, they know how often As with a 0 value on the first meaning dimension were
assigned a marker (and similarly for all other dimensions, values, and Os). On
the basis of these scores, rules may develop. If, for example, an agent finds
out that certain As virtually always turned out to
need marking, it may decide to do so straight away, irrespective of the
necessity in context (cf.
Durie's 1995 functional overkill; cf.
also Dolan and Dayan 2013, and Lestrade et al. 2016). Obviously, once a parent
generation decides to do this, the input language for the children becomes even
more skewed, increasing the probability for the next generation to make the
same generalization.
Note
that generalization can result in case-marking systems in which certain
intransitive subjects are marked too, for example marking them for their willful
involvement, as in Mongsen Ao discussed above: if marked As
happen to be almost always volitionally involved, their marker may become
associated with volitionality, because of which it is no longer primarily used
for disambiguation. If an S now is found to be exceptionally volitional, this
can be expressed using the original A marker. In terms of the model, if
virtually all marked As have a 1 on the third meaning
dimension, this meaning may trigger the use of A marking irrespective of
ambiguity and transitivity.
This
much technical background should suffice to appreciate the results of the
simulations discussed below. More information can be found in the help files of
the R package.
7. Present experiment
7.1 Underlying solution methods for resolving
ambiguity
In
the present experiment, the effect of different type of disambiguation
strategies will be investigated by manipulating the solutionMethod parameter that was developed for the purpose of the
present paper. As explained in the previous section, a speaker checks whether
the intended distribution of roles follows automatically from lexical semantics
or needs to be made explicit. For this, different strategies are conceivable.
In previous MoLE experiments, it was always the second argument that was marked
for its role in case of ambiguity, the idea being that the ambiguity only
becomes evident once this second participant is introduced, and only has to be
resolved there and then. But the role distribution could also,
and maybe more likely so, be made explicit by using the best marker available
in the lexicon, marking the worst performer, or randomly marking either of the
arguments. Other solution methods are conceivable and indeed possible to test,
such as marking only the internal argument, or both arguments. These strategies
seem to be less plausible, however, and therefore will not be considered here
(for example because internal roles are generalizations that first have to be
developed itself, and marking either of the arguments suffices to resolve
ambiguity, as observed in Section 2 already).
The
different types of language resulting from the different disambiguation
strategies that are investigated in this study are listed in (26). All other model parameters are held constant between lineages.
(26)
|
Disambiguation strategies
|
|
a.
|
Best marker (B):
use the best marker available
|
|
b.
|
Random
(R): mark either the A or O
|
|
c.
|
Second argument (S): mark the second argument
|
|
d.
|
Worst performer (W):
mark the worst performing participant
|
7.2 General results
Each solution type is tested with 6 lineages, each of which is run for
25 generations. As shown by the development of communicative success in Figure
2, three out of four lineages maintain a communicative-success rate of roughly
90% over time. This is as expected: The strategies themselves do not change
over time and the different strategies are all viable solutions in principle.
In the other 10% of the cases, the speaker wrongly believes the hearer should
be able to find out who does what to whom. This is most probably due to
changing lexical representations (because of desemanticization), because of
which the estimations of role qualifications may differ between agents.
Interestingly, however, this does not apply to the B lineages, in which
communicative success does increase over time.
Figure
2. Development of communicative success per strategy type over time.
(Each type is instantiated by six lineages. Dashed
lines show standard deviations).
Given the default noise settings and prominence over role distribution,
some form of role marking is used in approximately 42% initially in all
lineages (with a standard deviation of less than 4%; see Figure 3). As noted
above, this involves events in which one of the arguments qualifies at least
equally well for the other verb role, which is the case whenever the O argument
is equally prominent as or more prominent than the A argument (which, again, is
generally the case for prominent Os and non-prominent As).
As can be seen in Figure 3, this proportion remains stable over time in three
out of four lineages. In the B lineages, however, the use of case marking is
generalized beyond communicative necessity, because of which it becomes
obligatory eventually. As a result, the role distribution is always made
explicit, even if deemed unnecessary for disambiguation. Since this also
applies to the 10% of cases that are wrongly judged unambiguous, this leads to
maximal communicative success (cf. Figure 2).
Figure 3: Proportion of noun
marking per strategy type for the first and last generation.
(Only in the B lineages, the use of case marking
becomes generalized)
7.3 Emerging case systems
In the tables below, the case systems that have emerged under the
various solution strategies are shown. Case markers are identified as such if
they are used as role markers more than as referential expressions, if they
have lost all four of their non-binary meaning dimensions, and if their
production effort has fallen below the suffix threshold. The lin(eage) column shows the lineage, form gives the actual form and etymology shows the original form of the
marker. The freq(uency) column shows
the total frequency of use of the word in any function (out of the 2000
utterances used by the agent), and the NM column shows the usage as a noun
marker. The weight column shows the
proportion of dimensions that are still specified (recall that each word starts
out fully specified; the lower the weight, the more generalized the semantics).
The meaning column, finally, gives
the mean value on these remaining meaning dimensions. Again, higher values
correspond to actor properties and therefore markers with scores close to zero
can be understood as O markers (or “accusative cases”, once grammatical roles
are distinguished), whereas markers with scores close to one can be understood
as A markers (“ergative cases”).
Table 2 shows the result for the lineages of the random type (i.e. those
that randomly mark either of the arguments in case of imminent communicative
failure). As can be seen, all six lineages developed two role markers, one for
each generalized semantic role.
lin.
|
form
|
etymology
|
freq.
|
NM
|
weight
|
score
|
1
|
-po
|
pokynutuj
|
458
|
372
|
0.56
|
1
|
-yj
|
yfarunapow
|
490
|
394
|
0.56
|
0
|
2
|
-ub
|
umymirem
|
540
|
414
|
0.44
|
0
|
-ry
|
rylifupywy
|
367
|
301
|
0.56
|
1
|
3
|
-mi
|
mipumigo
|
438
|
369
|
0.56
|
1
|
-my
|
myfapyjes
|
415
|
335
|
0.56
|
0
|
4
|
-iw
|
ifakulihu
|
449
|
377
|
0.56
|
1
|
-ik
|
iwobyfufe
|
496
|
381
|
0.44
|
0
|
5
|
-hu
|
hywanarin
|
453
|
328
|
0.56
|
0.2
|
-ny
|
nyjanago
|
443
|
387
|
0.56
|
1.0
|
6
|
-ta
|
talodadahe
|
380
|
315
|
0.56
|
1
|
-sy
|
syjikogesu
|
508
|
390
|
0.44
|
0
|
Table 2:
Most frequently used noun markers of
lineages with random solution method.
[Lin(eage) gives the lineage; form shows the actual form and etymology
the original form of the marker; freq(uency) shows the total frequency of use
of a word (out of 2000 utterances), NM
the frequency of use as a noun marker. The weight column shows the
proportion of dimensions that are still specified (the lower the weight, the
more generalized the semantics); the meaning
column gives the mean value on these remaining meaning dimensions.]
Table 3 shows the case systems that develop under the second-argument
strategy. The results are very similar, except for the absence of a
dedicated case marker for the A role in the sixth lineage. This absence follows
from the technical requirements that markers should no longer be specified for
a non-binary meaning dimension. Because of this, the suffix -ro,
which otherwise is a perfect A marker but still has one such specification, is
not listed.
lin.
|
form
|
etymology
|
freq.
|
NM
|
weight
|
score
|
1
|
-py
|
pijyfiwud
|
220
|
178
|
0.56
|
1
|
-af
|
afutomabuj
|
647
|
489
|
0.44
|
0
|
2
|
-oh
|
ohusamido
|
628
|
533
|
0.44
|
0
|
-om
|
omypyhub
|
240
|
184
|
0.56
|
1
|
3
|
-ub
|
uwegaser
|
257
|
197
|
0.56
|
1
|
-ku
|
kuheleki
|
626
|
534
|
0.44
|
0
|
4
|
-if
|
ifinygobis
|
625
|
538
|
0.44
|
0
|
-as
|
asunilare
|
222
|
159
|
0.56
|
1
|
5
|
-my
|
mygutawil
|
646
|
525
|
0.44
|
0
|
-im
|
imisilet
|
291
|
228
|
0.56
|
1
|
6
|
-ym
|
ymisadigi
|
606
|
493
|
0.44
|
0
|
Table 3: Results for lineages with second-argument strategy.
Also the
results for the lineages that resolve ambiguity by marker the worst performer
are largely equivalent to the previous ones. Each lineage developed markers for
both roles, using them roughly equally often.
lin.
|
Form
|
Etymology
|
freq.
|
NM
|
weight
|
score
|
1
|
-yk
|
yharenyp
|
489
|
364
|
0.44
|
0
|
-no
|
nubiwewym
|
441
|
368
|
0.56
|
1
|
2
|
-by
|
balapygu
|
413
|
333
|
0.56
|
1
|
-be
|
betifofup
|
455
|
391
|
0.56
|
0
|
3
|
-uh
|
uniharij
|
494
|
388
|
0.56
|
1
|
-yb
|
ybihowab
|
460
|
363
|
0.56
|
0
|
4
|
-ak
|
awigarynu
|
503
|
370
|
0.56
|
0
|
-oj
|
ohetuwur
|
334
|
282
|
0.56
|
1
|
5
|
-ud
|
udolujef
|
392
|
314
|
0.56
|
1
|
-ag
|
arasipew
|
507
|
371
|
0.44
|
0
|
6
|
-gy
|
gynadobo
|
470
|
394
|
0.56
|
0
|
-ig
|
ifibiwetaf
|
454
|
324
|
0.56
|
1
|
Table 4: Results for lineages with worst-performer strategy.
The results of the best-marker lineages
are qualitatively very different from the other three lineages. Most
strikingly, only one type of case marker developed per lineage. Since it is always the best marker that is
selected, a small initial advantage may lead to exclusive usage. As was
observed in Figure 3 already, the use of these markers becomes generalized
beyond communicative necessity only for this type of lineage. Because of this,
these markers are much more frequent than the markers in the other lineages.
And as a result, they are all maximally desemanticized. Whereas some of the
previous markers have a semantic weight of .56; here, all markers are at .44.
lin.
|
form
|
etymology
|
freq.
|
NM
|
weight
|
score
|
1
|
-uh
|
uhemabir
|
1782
|
1609
|
0.44
|
0
|
2
|
-ab
|
anoruduwim
|
1677
|
1511
|
0.44
|
0
|
3
|
-ji
|
jikemywo
|
1639
|
1518
|
0.44
|
0
|
4
|
-ih
|
ihifysowa
|
1433
|
1341
|
0.44
|
1
|
5
|
-ow
|
owupahywyk
|
1756
|
1603
|
0.44
|
0
|
6
|
-op
|
opelotato
|
1759
|
1602
|
0.44
|
0
|
Table 5: Results for lineages with best-marker strategy.
7.4 Disambiguation of semantic roles in
artificial languages
In the previous sections, it was explained how the distribution of
semantic roles is disambiguated in the various lineages, and what types of case
systems emerge from this over time. In this section, some concrete examples of
the end results in the different lineages are provided. To construct these examples, the argument structure of a proposition
that led to a marked expression is simply reversed, after which the speaker
agent develops a new utterance for that meaning. (Using example [3]: if a
speaker uses role marking to make explicit that it really is a pig killing a
woman, how do they express a woman killing a pig?) Recall that no case marking
is available whatsoever initially (cf. [23]), word order is not informative at
any time, and translations can only give an idea of the argument structure, as
the meanings cannot be translated beyond their numerical representations (which
would not be of much help for intelligibility).
In (27),
an example from one of the R lineages is given, in which it is randomly
determined which of the arguments is marked if the role distribution does not
follow automatically. Opifep (say
‘pig’) is a much better performer of the O role of the verb oli (‘kill/bite’) than of its A role (as
can be seen when checking the respective typing scores of .78 and 42), and,
equally importantly, a much better performer of the O role than the other
argument huwenahe (‘woman’, with a
score of .54). Without explicit
marking, then, the interpretation is that opifep
is oliing rather than being olied, as shown in (27a).
To overrule this default interpretation, explicit marking of the role
distribution has to be used. Given the
random solution strategy of this lineage, this could either involve marking opifep for its A role, using the A
marker -po (27b) or marking huwenahe for its O role, by means of the
O marker -yi (27c). Again, these
markers were not available in the beginning, but developed as a result of
erosion and desemanticization in the course of the simulation only.
(27)
|
Random marking
|
|
a.
|
opifep
|
oli
|
huwenahe
|
|
|
opifep
|
oli.V
|
huwenahe
|
|
|
‘Huwenahe olies opifep.’ (cf. the woman killed pig)
|
|
|
|
|
b.
|
opifep-po
|
oli
|
huwenahe
|
|
|
opifep-A
|
oli.V
|
huwenahe
|
|
|
‘Opifep olies huwenahe.’ (cf. the
pig bit the woman)
|
|
|
c.
|
opifep
|
oli
|
huwenahe-yj
|
|
|
opifep
|
oli.V
|
huwenahe-O
|
|
|
‘Opifep olies huwenahe.’ (cf. the
pig bit the woman)
|
(28)
|
Second argument
|
|
a.
|
kalakip
|
sobojifehy
|
wywakak
|
|
|
kalakip
|
sobojifey.V
|
wywakak
|
|
|
‘Wywakak sobojifeyes kalakip.’
|
|
|
b.
|
kalakip
|
sobojifehy
|
wywakak-af
|
|
|
kalakip
|
sobojifey.V
|
wywakak-O
|
|
|
‘Kalakip sobojifeyes wyakak.’
|
|
|
c.
|
wywakak
|
kalakip-am
|
sobojifehy
|
|
|
wywakak
|
kalakip-A
|
sobojifey.V
|
|
|
‘Kalakip sobojifeyes wyakak.’
|
|
|
|
|
|
|
|
The lineages of the W type always mark the worst-performer if
disambiguation is necessary. The minimal
pair in (29a,b) shows the use of the O marker -yk. If it is the performer of the A
role that qualifies worst instead, the A marker -no can be used, as shown in (29c).
(29)
|
Worst
performer
|
|
a.
|
ro
|
dadises-yk
|
habages
|
|
|
ro.V
|
dadises-O
|
habages
|
|
|
‘Habages
roes dadises.’
|
|
|
b.
|
ro
|
dadises
|
habages
|
|
|
ro.V
|
dadises
|
habages
|
|
|
‘Dadises
roes habages.’
|
|
|
c.
|
onoteuk
|
dywes-no
|
lahogohe
|
|
|
onoteuk.V
|
dywes-A
|
lahogohe
|
|
|
‘Dywe
onoteuks lahogoe.’
|
|
|
|
|
|
|
|
|
Differently from all lineages of the previous types, the lineages using
a best-marker strategy all generalized their use of case marking. As a result,
both O arguments of the minimal pair in (30) receive case marking, irrespective
of their role qualifications and irrespective of any possible ambiguity.
(30)
|
Best marker
|
|
a.
|
jajuhup
|
yhimomyd-uh
|
ygoj
|
|
|
jajuhupuh
|
yhimomyd-O
|
ygoj.V
|
|
|
‘Jajuhupuh ygojes yhimomyd.’
|
|
|
|
|
b.
|
Jajuhup-uh
|
yhimomyd
|
ygoj
|
|
|
Jajuhup-O
|
yhimomyd
|
ygoj.V
|
|
|
‘Yhimomyd ygojes jajuhupuh.’
|
|
|
|
|
|
|
|
Interestingly, generalization in the best-marker lineages leads to a use
of agentive case marking comparable to the PMA marking discussed in Section 3.
For example in (31), the intransitive subject is
marked for its actorhood, where there obviously is no role ambiguity possible:
(31)
|
yluweju-ih
|
uryboroju
|
|
yluweju-A
|
uryboroju
|
|
‘Yluweju uryborojues.’
|
In the previous sections it was shown how case marking may emerge in
artificial computer languages in which initially only lexical means are
available. Different solution methods for disambiguation that could be
hypothesized to underlie the eventual use of case marking were tested.
Intuitively, the strategy to randomly mark either of the arguments seems least
plausible. That is, it can be assumed that in the absence of grammatical rules,
speakers still use a culturally determined convention as to how to say things
properly. Cross-linguistically, next, it seems the strategy to always mark the
second argument is not very likely either: As far as we know, no such
correlation has ever been reported in the typological literature. Instead,
there is something to say for the other two strategies: as for the best-marking
strategy, it seems a valid linguistic procedure to reuse solutions that have
proven to work before previously, whereas the worst-performer strategy squares
well with independently motivated relevance
principles, which say to mark features on the relevant constituents (cf.
Malchukov 2006). Empirically, it seems, the best-marker strategy gave the best
results. As far as we know, most natural languages develop only one type of
case marking for either generalized role, not for both. Moreover, it resulted
in case marking very comparable to PMA marking in TB. Instead, all but the
best-marker lineages developed both types of marking, making them less likely.
Note that at the same time, however, most languages do not seem to generalize their use of case marking across the board
(Sinnemäki 2014), suggesting a counterforce that is not properly presented in
the model (yet).
Obviously, such findings should be treated with care indeed and the
results model cannot be translated to natural-language change directly. For
example, the solution strategies should probably be considered stochastic and
interacting rather than absolute and mutually exclusive parameters. Also,
alternative marking strategies (such as word order or verb marking), and person
distinctions (on the basis of which different marking systems may develop)
should be taken into consideration (as is done in current experiments).
Nevertheless, it is important to notice that the emergence of case marking can
be modeled as resulting from a clear pragmatic motivation, which nicely
corresponds to the findings in natural language discussed in the first part of
the paper.
As a final point of discussion, the predominance of O marking in the
best-marker lineages should be mentioned. This could be merely coincidence, of
course, and six lineages are not enough to tell whether one is more likely than
the other. Cross-linguistically, at least, there seems to be no clear
preference for either type of marking. If the preference for O marking in the model
is found genuine, this means disambiguation is not enough to explain the
emergence of case marking.
8. General conclusions
In this paper we discussed the development of case marking in
Tibeto-Burman and artificial computer languages. Our fundamental conclusion is
that the purpose of the agentive marking is disambiguation, which develops from
the innovative use of a more concrete (spatial) marker in a metaphorically
extended core function. Our survey also shows that pragmatically motivated case
marking is more widespread in TB languages than was previously appreciated.
Examples were given of uses to disambiguate semantic roles in bivalent clauses;
for contrastive reference, i.e. to pragmatically distinguish a referent from
one or more other potential referents, or to foreground a referent; to encode
extraordinary, willful, or atypical behavior, especially in the context of an
unexpected turn of events; to clarify the semantic role of a remaining core
argument when another core argument undergoes ellipsis; to distinguish the
causer argument in causativized clauses, and to characterize a habitually
acting NP referent. In the simulation experiment, several underlying strategies
that may lead to the development of pragmatically motivated case marking were
tested. It was shown that a strategy that employs the best marker available
leads to the most promising results.
Acknowledgements
We are grateful to two anonymous reviewers for their suggestions and
comments on an earlier draft, but fully absolve them of responsibility for the
analysis and conclusions. Research by Coupe for this paper was generously
supported by an Alexander von Humboldt Fellowship for Experienced Researchers
(2016–2018), and a Singapore Government Ministry of Education AcRF Research
grant (MOE 2016-T1-001-220). Research by Lestrade was supported by the
Netherlands Organisation for Scientific Research (NWO; grant 275-78-001).
Abbreviations
abl
|
ablative
|
evid
|
evidential
|
nrl
|
non-relational noun prefix
|
abs
|
absolutive
|
ex
|
existential
|
nzp
|
nominalizing prefix
|
anaph
|
anaphoric demonstrative
|
exclm
|
exclamation
|
obl
|
oblique
|
aor
|
aorist
|
f
|
feminine
|
onom
|
onomatopoeia
|
assure
|
assurance particle
|
fgr
|
foregrounder
|
ord
|
ordinal
|
aux
|
auxiliary
|
gpn
|
generic pronoun
|
pfv
|
perfective
|
agt
|
agentive
|
hm
|
hesitation/pause marker
|
pl
|
plural
|
caus
|
causative
|
hon
|
honorific
|
pol
|
polite particle
|
com
|
comitative
|
imm
|
immediate future tense
|
poss
|
possessive
|
compar
|
comparative derivation
|
inst
|
instrumental
|
prox
|
proximate demonstrative
|
cont
|
contrastive
|
irr
|
irrealis mood
|
part
|
participle
|
cond
|
conditional
|
ln
|
loan word
|
pres
|
present tense
|
cop
|
copula
|
lnmlz
|
locative nominalizer
|
pst
|
past tense
|
cvb
|
converb
|
loc
|
locative
|
ptcl
|
speech act particle
|
decl
|
declarative
|
loc.cvb
|
locative converb
|
red
|
reduplication
|
dat
|
dative
|
mid
|
middle
|
rpet
|
repetitive aspect
|
dir
|
direction
|
mir
|
mirative
|
seq
|
sequential converb
|
dist
|
distal demonstrative
|
neg
|
negative
|
sg
|
singular
|
dm
|
discourse marker
|
nf
|
non-finite
|
sim
|
simultaneous converb
|
dur
|
durative
|
nhyp
|
non-hypothetical
|
vis
|
visual (direct) evidential
|
ego
|
egophoric
|
nmlz
|
nominalizer
|
voc
|
vocative
|
emphat
|
emphatic
|
nprox
|
non-proximate
|
|
|
eq
|
equational
|
npt
|
non-past
|
|
|
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|
Person
|
Role
|
1
|
2
|
prominent 3
|
non-prominent 3
|
Subject
|
38%
|
22%
|
33%
|
7%
|
Direct object
|
3%
|
3%
|
10%
|
84%
|
Note
that the absence of a cross-linguistic preference for O marking could be used
to further argue against the W and S strategies. Given the Dahl numbers of
Table 1, most confusion is due to prominent Os (viz. .93x.16 vs .07x.84). Under
a worst-performer strategy, O marking should then be more likely to develop
than A marking. Indeed, in most W lineages, O seems more frequent than A
marking (cf. Table 4), although it would require further investigation to show
this effect is statistically significant. (This reasoning does not apply to the
B type, which does not care about the source of the confusion but only
considers the best solution.) As for the S strategy: if word order played a
role in the simulations (which it does in current MoLE experiments, as it does
in natural languages; cf. the first part of this paper), O marking should be
predominant too, since As tend to appear before Os cross-linguistically.