Extracting Semantic Roles from a Model of Eventualities 
Sylvie Ratt6 
Universit6 du Qu6bec fi MontrSal / Linguistics Department 
C.P. 8888, Succ. "A" / Montreal, QC / H3C 3P8 
e-mail: sr@info.uqam.ca 
The notion of semantic roles is usually at- 
tributed to Fillmore \[8\], however its history can 
be traced back through TesniSre \[16\] to Panini. 
Following this tradition, many researchers rec- 
ognize their usefulness in the description of 
language -- even if they do not agree on their 
significance \[7\]. However, a weak or strong 
commitment to this notion does not elude the 
fact that it proves to be very difficult to settle on 
a finite set of labels along with their formal def- 
initions. The dilemma resulting from this 
challenge is well known: to require a univocal 
identification by each role results in an increase 
in their number while to abstract their semantic 
content gives rise to an inconsistent set. If a fi- 
nite set is possible, one has to find a proper 
balance between these two extremes. As a result, 
every flavor of roles have been used from time to 
time in linguistics (e.g., GB, in the spirit of 
Fillmore, HPSG, in the line of situation seman- 
tics), and also in AI \[10, see also 4\]. 
Between the total refusal to use those labels 
(as in GPSG) and the acceptance of individual 
roles (as in HPSG) there is a wide range of pro- 
posals on what constitute a good set of 
L(inguistic)-Roles \[7\] and, as a consequence, on 
the way to differentiate between them and define 
them. Most of the definitions have been based on 
the referential properties that can be associated 
with each role bearer (e.g. an AGENT is a 
volitional animate entity). Even if this approach 
is necessary at one time or another, this kind of 
definition inevitably leads to either the "let's 
create another role" or the "let's abstract its 
definition" syndromes. Properties are not always 
of the static kind though. Sometimes, dynamic 
properties are also used (e.g. an AGENT is the 
perceived instigator of the action). 
Since one of the desired characteristic of a 
roles system is the power to discriminate events 
\[5\] (another "desired" property being to offer an 
easier selection of grammatical functions), the 
recognition of semantic roles should be linked to 
the interpretation of the event, that is to their dy- 
namic properties. In a study on locative verbs in 
French, Boons \[3\] has convincingly shown the 
importance of taking into account aspectual cri- 
teria in the description of a process, suggesting 
that GOAL and SOURCE roles should be reinvesti- 
gated in the light of those criteria. It is our 
hypothesis that proliferation of roles is a natural 
phenomenon caused by the specialized proper- 
ties required by the interpretation of a predicate 
within a specific semantic field: to overlook 
these properties yields the over-generalization 
already mentionned. The best way to approach 
the expansion/contraction dilemma is to search 
for the minimal relations required for a dynamic 
interpretation of events (in terms of their aspec- 
tual criteria and through an identification of all 
the participants in i0. 
Our first step toward this abstraction was to 
consider each participant (individuals or 
properties) either as a localized entity (a token) 
or a location (a place), and to determine its role 
in the realization of the process expressed by the 
predicate. The model exhibits some common 
points with a localist approach \[1,11\] since it 
recognizes (in an abstract sense) the importance 
of spatio-temporal "regions" in the process of 
individuation of events \[14\]. To express the 
change of localization (again in an abstract 
sense), the notion of transitions is used. The 
entire construction is inspired by Petri net theory 
\[15\]: a set S of places, a set T of transitions, a 
flow relation F: (S x T) ~ (T x S) and markers 
are the categories used to define the structure of 
a process (and as a consequence of the events 
composing it). 
For example, the dynamic representation of 
Max embarque la caisse sur le cargo \[3J/Max em- 
barks the crate on the cargo boat can be analyzed 
in two steps. First there is a transition from an 
initial state IS where the crate is not on the cargo 
boat to a final state FS where the crate is on the 
cargo boat. The final state can be expressed by 
the static passive, la caisse est embarqude sur le 
cargo~the crate was embarked on the cargo boat, 
and is schematized in (2). One of the argument 
(cargo boat) is used as a localization while the 
other argument is used as a localized entity 
(crate), the THEME according to Gruber \[9\]. The 
initial state can be expressed (in this case) by the 
negation of the final state and is schematized in 
(1). The realization of the entire process is then 
represented by the firing of the net which can be 
illustrated by the snapshots (1) and (2). 
1. Is:t~ir-~O:Fs 2. IS:O---\[---(~):Fs 
To integrate the participation of "Max" in 
the model, we recognize the importance of 
335 
causality in the discrimination of events \[13,14\]. 
Since the cause is understood to be the first 
entity responsible for the realization of events 
\[6\], the obvious schematization is (3). 
3. 4. 
It is possible that a recursive definition 
(places and transitions) will be necessary to ex- 
press "properly" the causation, the localization 
of events and processes or the concept of dy- 
namic states \[2,14\]. In that case, the schematiza- 
tion could then be (4). But we can achieve the 
same result through a proper type definition of 
the transition expressing the cause: (s x 0 -~ (t x 
((s x t) -, (t x s))), where "s" is a place and "t", a 
transition. 
This approach to semantic roles determina- 
tion is close to the one undertook by Jackendoff 
\[12\]. His identification of each role to a particu- 
lar argument position in a conceptual relation is 
given here by the way it participate to the firing 
of the net. (It is our guess that most of the con- 
ceptual relations used by Jackendoff can be 
expressed within this model, giving to them an 
operational interpretation.) The model has the 
advantage to give an explicit and simple defini- 
tion of relations that do not have the same 
semantic range (e.g. CAUSE vs FROM vs AT). 
The analysis of locative processes using 
abstract regions instead of the traditional roles is 
better because it is, we think, the real basis of 
those interpretations. Abstracting away referen- 
tial properties gives the basic interactions ex- 
pressed by the predicate. Specifying those 
properties within a specific semantic field gives 
rise to the set of roles we are used to (e.g. within 
the spatial field, schematizations (1) and (2) 
express SOURCE and GOAL roles). 
With this model we were able to give an 
operational description of the difference between 
Max charge des briques dans le camion/Max 
loads bricks in the truck and Max charge le 
camion de briques/Max loads the truck with 
bricks. The schematization take into account 
which participant is responsible for each transi- 
tion firing and thus can lead us to the "final" 
place. As a first approximation of these continu- 
ous processes, (5) and (6) are proposed (the 
direct contribution of the instrument is also 
introduced). But recognition, as a participant of 
the quantity of bricks in (5) and the capacity of 
the truck in (6), results in the schematizations (7) 
et (8) (both display a specialization of their 
direct object in order to complete the semantic 
interpretation). 
. :b'uckl5. J :WuokFS 
'.Max :bdch IS :Initial F$ 5. ,~,,~a -~, 6. 
7. ~ath,=~t .~J~ 8. 
By its simplicity, the model can thus give 
rise to "confusion" over some roles, in accor- 
dance with the general tendancy to observe 
"roles clusters". The resulting notation seems 
also an interesting way to explore the differences 
between static and dynamic processes, differ- 
ences that are not very '~,isual" if one is using a 
static notation. 
Our research is now directed toward the 
analysis of the system when more semantic 
content is used. We are testing if these adds-on 
have impacts on its behaviour, while analyzing if 
the partial semantic interpretation gives rise to 
the predicted syntactic forms (that is how does 
each potential participant is grammaticalized). 

References 
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