Conceptual and Linguistic Decisions in Generation 
Laurence DANLOS 
LADL (CNRS) 
Universit~ de Paris 7 
2, Place Jussieu 
7S00S Paris, France 
ABSTRACT 
Generation of texts in natural language requires making 
conceptual and linguistic decisions. This paper shows first that 
these decisions involve the use of a discourse grammar, 
secondly that they are all dependent on one another but that 
there is a priori no reason to give priority to one decision 
rather than another. As a consequence, a generation 
algorithm must not be modularized in components that make 
these decisions in a fixed order. 
1. Introduction 
To express in natural language the information given in a 
semantic representation, at least two kinds of decisions have to 
be made: "conceptual decisions" and "linguistic decisions". 
Conceptual decisions are concerned with questions such as: in 
what order must the information appear in the text? which 
information must be expressed explicitly and what can be left 
implicit? Linguistic decisions deal with questions such as: 
which lexical items to choose? which syntactic constructions to 
choose? how to cut the text into paragraphs and sentences? 
The purpose of this paper is to show that conceptual 
decisions and linguistic decisions cannot be made 
independently of one another, and therefore, that a generation 
system must be based on procedures that promote intimate 
interaction between conceptual and linguistic decisions. In 
particular, our claim is that a generation process cannot be 
modularized into a "conceptualizer" module making conceptual 
decisions regardless of any linguistic considerations, passing its 
output to a "dictionary" module which would figure out the 
lexical items to use accordingly, which would then in turn 
forward its results to a "grammar", where the appropriate 
syntactic constructions are chosen and then developed into 
sentences by a "syntactic component". In such generation 
systems (cf. (McDonald 1983) and (McKeown 1982)), it is 
assumed that the conceptualizer is language-free, i.e., need 
have no linguistic knowledge. This assumption is questionable, 
as we are going to show. Furthermore, in such modularized 
systems, the linguistic decisions must, clearly, be made so as 
to respect the conceptual ones. This consequence would be 
acceptable if the best lexical choices, i.e., the most precise, 
concise, evocative terms that can be chosen, always agree 
with the conceptual decisions. However, there exist cases in 
which the best lexical choices and the conceptual decisions are 
in conflict. 
To prove our theoritical points, we will take as an 
example the generation of situations involving a result 
causation, i.e., a new STATE which arises because of one (or 
several) prior ACTs (Schank 1975). An illustration of a result 
causation is given in the following semantic representation 
(A) CRIME : ACT =: SHOOTING 
ACTOR --> HUMO =: 3ohn 
SHOOTING:AT --> HUMI =: Mary 
BODY-PART =: HEAD 
===> STATE =: DEAD 
OB3ECT --> HUMI 
which is intended to describe a crime committed by a person 
named John against a person named Mary, consisting of 
John's shooting Mary in the head, causing Mary's death. 
2. Conceptual decisions and lexical choice 
Given a result causation, one decision that a 
language-free conceptualizer might well need to make would 
be whether tO express the STATE first and then the ACT, or to 
choose the opposite order. If these decisions were passed on 
to a dictionary, the synthesis of (A) above would be texts like 
Mary is dead because John shot her in the head. 
John shot Mary in the head. She is dead. 
made up of one phrase expressing the STATE and one 
expressing the ACT. But it seems more satisfactory to produce 
texts such as 
( Z ) Mary was killed by John. He shot her in the head. 
(2) John shot Mary in the head, killing her. 
built around to kill. Such texts don't follow conceptual 
decisions dissociating the STATE and its cause: to kill (in the 
construction No V N1 =: John killed Mary) expresses in the 
same time the death of N1 and the fact that this death is due 
to an action (not specified) of No (McCawley 1971). We 
showed in (Danlos 1984) that a formulation embodying a verb 
with a causal semantics such as to kill to describe the 
RESULT, and another verb to describe the ACT is, in most of 
the cases, preferable to a formulation composed of a phrase 
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for the STATE and another one for the ACT. This result 
indicates that conceptual decisions should not be made without 
taking into account the possibilities provided by the language, 
in the present case, the existence of verbs with a causal 
semantics such as to kill, This attitude is also imperative if a 
generator is to produce frozen phrases. The meaning of a 
frozen sentence being not calculable from the meaning of its 
constituents, frozen phrases cannot be generated from a 
language- free conceptualizer forwarding its decisions to a 
dictionary 
\]1. Conceptual decisions, segmentation into sentences and 
syntactic constructions 
Let us suppose that a result causation is to be 
generated by means of two verbs, one with a causal semantics 
such as to kill for the RESULT, and one for the ACT, and let 
us look at the ways to form a text embodying these two 
verbs. The options available are the following: 
- order of the information. There are two possibilities. Either 
the phrase expressing the RESULT or the phrase expressing 
the ACT occurs first. 
- number of sentences. There are two possibilities. Either 
combine the phrases expressing the RESULT and the ACT into 
a complex sentence, as in (2) (John shot Mary in the head, 
killing her.), or form a text made up of two sentences, one 
describing the ACT, one describing the RESULT, as in (1) (Mary 
was killed by John. He shot her in the head.). 
- choice of syntactic constructions. We will restrict ourselves 
to the active construction and to the passive one. For the 
latter, there is the choice between passive with an agent and 
passive without an agent. On the whole, for each of the two 
verbs involved, there are three possibilities. 
The combination of these 3 options gives 36 possibilities, but it 
turns out that only 15 of them are feasible. For example, 
texts composed of two sentences, one in a passive form with 
an agent, the other in a passive form without an agent, are 
appropriate to 
precedes the 
expressing the 
(3a) Mary 
( 3b ) Mary 
(3c) Mary 
(3d) *Mary 
express a result causation only if the RESULT 
ACT, or if the agent is in the first sentence 
ACT: 
was killed by John. She was shot. 
was killed. She was shot by John. 
was shot by John. She was killed. 
was shot. She was killed by John. 1 
As another example, it is possible to combine the phrases 
expressing the ACT and the RESULT into a complex sentence if 
they are both in an active form 
John shot Mary, killing her. 
John killed Mary by shooting her. 
but it is impossible if they are both in a passive form: the 
following formulations are awkward 
*Mary was killed by being shot by John. 
*Mary was killed by John by being shot. 2 
and the only other conceivable possibilities are to use a 
subordination conjunction such as because, when or as, but 
the resulting texts are clumsy: 
*Mary was killed (because + when + as) she was 
shot by John. 
*Mary was shot by John and, because of that, she was 
killed. 
A generation system must know for each combination 
whether it is feasible or not. Either this knowledge is 
calculable from other data, or it constitutes data that must be 
provided to the generator. We are going to see that the 
second solution is better. First, on a semantic level, one can 
seek to verbalize the intuitions that can be drawn, for example, 
from paradigm (3), but this activity can be only descriptive and 
not explicative. In other words, the inacceptability of (3d) is a 
fact of language that cannot be explained by semantic 
computations of more general import. So the list of the 15 
feasible combinations must be part of the data of the 
generator. Now the following question arises: is it possible to 
determine the structures of the texts corresponding to the "15 
elements of this list. The answer is affirmative when the 
number of sentences is 2, and negative when it is 1. The 
combinations with two sentences involve only one type of 
linearization: juxtaposition. On the other hand, the 
combinations with one sentence involve 
- a present participle if the ACT and RESULT are both 
expressed in an active form and if the ACT precedes the 
RESULT, as in John shot Mary, killing her 
- a gerundif if the ACT and the RESULT are both expressed 
in an active form and if the RESULT precedes the ACT, as in 
John killed Mary by shooting her 
1. A star (') indicates that a text is awkward but it does not necessarily mean 
that it is ungrammatical Or uninterpretable. 
2. The deletion of the agent leads to a formu\]abon which is correct Mary was 
killed by being shot but which does not express the author of the crime. 
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- a relative clause if the RESULT is expressed in a passive 
form with an agent and precedes the ACT, this being 
expressed in an active form, as in Mary was killed by John 
who shot her in the head 
- etc. 
These types of linearization are nOt predictable. As a 
consequence, they must be provided to the generator. This 
one must embody in its data the structures of the texts 
corresponding to the 15 feasible combinations. These 
structures constitute a real discourse grammar for result 
causations. The formulation of result causations must be 
modelled on one of the 15 discourse structures 3. Generating 
a result causation thus entails selecting one of these discourse 
structures. 
~.. Selection of a discourse structure 
The fact that only 15 discourse structures out of 36 
possibilities are feasible shows that it is not possible to make 
decisions about order of information, segmentation into 
sentences and syntactic constructions independently of one 
another. To do so could potentially result in awkward texts 
more than half the time. 
Furthermore, lexical choice and selection of a discourse 
structure cannot be made independently of one another. A 
discourse structure leads to an acceptable text if and only if 
the formulations of the ACT and the RESULT present the 
syntactic properties required by the structure. For example, 
some causal verbs such as to assassinate cannot occur after a 
phrase describing the ACT: 
*John shot the Pope in the head assassinating him. 
*John shot the Pope in the head. He assassinated 
him 4 . 
So, if the verb to assassinate is to be used, all of the 
3. This point is akin to an assumption supported by (McKeown 1982), except 
that ours discourse structures contain linguistic information contrarily to hers 
which indicate only the order in which the information must appear. 
4. These forms become acceptable if they are added adverbial phrases: 
John shot the Pope in the head, thereby assassinating Aim in a 
spectacular way. 
John shot the Pope in the head. Thereby he assassinated him in a 
spectacular way. 
discourse structures in which the RESULT appears after the 
ACT are inappropriate. On the other hand, if a discourse 
structure where the RESULT occurs after the ACT is selected, 
the use of to assassinate is forbidden. 
At this point, we have shown that decisions about lexical 
choice, order of the information, segmentation into sentences 
and syntactic constructions are all dependent on one another. 
This result is fundamental in generation since it has an 
immediate consequence: ordering these decisions amounts to 
giving them an order of priority. 
$'. Priorities in decisions 
There is no general rule stating to which decisions 
priority must be given. It can vary from one case to another. 
For example, if a semantic representation describes a suicide, 
it is obviously appropriate to use to commit suicide. To do 
so, priority must be given to the lexical choice and not to the 
order of the information. If the order ACT-RESULT has been 
selected, it precludes the use of to commit a suicide which 
cannot occur after the description of the act performed to 
accomplish the suicide: 
*John shot himself, committing suicide. 
*John shot himself. He committed suicide. 
On the other hand, if a result causation is part of a bigger 
story, and if strictly chronological order has been chosen to 
generate the whole story, then the result causation should be 
generated in the order ACT-RESULT. In other words, the order 
of the information should be given priority. In other situations, 
there is no clear evidence for giving priority to one decision 
over another one. As an illustration, let us take the case of a 
result causation which occurs in the context of a crime. It can 
be stated that the result DEAD must be expressed by: 
- to assassinate as a first choice, to kill as a second 
choice, if the target is famous 
- to murder as a first choice, to kill as a second 
choice, if the target is not famous 
Moreover, the most appropriate order is, in general, 
RESULT-ACT if the target is famous, and ACT-RESULT 
otherwise. In the case of a famous target, the use of to 
assassinate is not in contradiction with the decision about the 
order of the information. But in the case of a non-famous 
• arget, the use of to murder doesn't fit the order ACT-RESULT, 
for this verb cannot occur after a description of the ACT: 
• John shot Mary in the head, murdering her. 
• John shot Mary in the head. He murdered her. 
Therefore, either the decision about the order of the 
information or the decision to use to murder has to be 
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forsaken. The former solution would yield to texts such as 
John murdered Mary by shooting her in the head. 
John murdered Mary. He shot her in the head. 
where the order of the information is RESULT-ACT, and the 
latter one to texts such as 
John shot Mary in the head, kilting her. 
John shot Mary in the head. He killed her. 
using the verb to kill instead of to murder. At the current 
time, the choice between these two solutions can be based 
only on intuitions that are not sufficiently operational to be 
integrated in a generation system. 
Condusion and future research 
We have shown that decisions about lexical choice, 
determination of the order of the information, segmentation into 
sentences and choice of syntactic construction are all 
dependent one another, the last three amounting to the 
selection of a discourse structure by means of a discourse 
grammar. As a consequence, a generation system must be 
based on a complete interaction between these decisions. In 
this work, we have been concerned only with the task of 
expressing into natural language a set of information. In 
others words, we have only dealt with the generation problem 
of "How to say it?", and not with the problem "What to say?". 
Some authors (cf. (McGuire 1980) and (Appelt 1982)) have 
rejected the separation between "What to say" and "How to 
say it" on the basis that the issue of "What to say" is not 
independent from the lexical choice. Thus, they have argued 
for generation systems involving interactions between 
conceptual decisions and linguistic ones. This point is akin to 
ours, and therefore, our model of generation could be 
extended so as to treat issues such as generating different 
texts according to the hearer and what it is supposed that he 
wants and/or needs to hear. 
REFERENCES 
Appelt, D.E., 1982, Planning Natural-Language Uterrances to 
satisfy Multiple Goals, Technical Note 259, SRI 
International, Menlo Park, California. 
Danlos, L., 1984, Generation automatique de textes en langues 
naturelles, These d'Etat, Universit~ de Paris 7. 
McCawley, J. D., 1971, "Prelexical Syntax" in Report of the 
22nd annual round table meeting on Linguistics and 
Language Studies, O'Brien ~d., Georgetown University 
Press. 
McDonald, D., 1983, "Natural Language Generation as a 
Computational Problem : an introduction", in 
Computational Models of Discourse, Brady et Berwick 
ads., MIT Press, Cambridge, Massachussets. 
McGuire, R., 1980, "Political primaries and words of pain", 
unpublished manuscript, Yale University. 
McKeown, K. R., 1982, Generating Natural Language Text in 
response to Questions about database structure, PhD 
D=ssertation, University of Pensylvania. 
Schank, R.C., 1975, Conceptual Information Processing, North 
Holland, Amsterdam. 
ACKNOWLEDGEMENTS 
I would like to thank Lawrence Birnbaum for many valuable 
discussions and suggestions on this paper. 
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