International audienceThis paper deals with the processing of a formal electronic dictionary of French centered around the description of semantic derivations and collocations. The purpose of our project was to obtain a more flexible format for this dictionnary, the DiCo, which has a traditional structure. By compiling the DiCo, we get an object model which, in turn, can be stored in an SQL database. We show how the object model allows us to more easily access the data and gives us a new perspective on the structure of dictionary. This latter can be completly reorganized following new axes like lexical function links

Kahane, Sylvain

Polguère, Alain

Steinlin, Jacques

Archive Ouverte en Sciences de l'Information et de la Communication

HAL Id: halshs-00120390
https://halshs.archives-ouvertes.fr/halshs-00120390
Submitted on 20 Sep 2019
HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.
L’archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d’enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.
Compiling a “classical” explanatory combinatorial
lexicographic description into a relational database
Jacques Steinlin, Sylvain Kahane, Alain Polguère
To cite this version:
Jacques Steinlin, Sylvain Kahane, Alain Polguère. Compiling a “classical” explanatory combinato-
rial lexicographic description into a relational database. Conference on the Meaning Text Theory
(MTT’2005), 2005, Moscou, Russia. pp.1. ￿halshs-00120390￿
Compiling a "classical" explanatory combinatorial lexicographic
description into a relational database
Jacques Steinlin†, Sylvain Kahane†, Alain Polguère‡
† LaTTice – Université de Paris 7, ‡ OLST – Université de Montréal
jsteinli@linguist.jussieu.fr, sk@ccr.jussieu.fr, alain.polguere@umontreal.ca
Abstract
This paper deals with the processing of a formal electronic dictionary of French centered around the
description of semantic derivations and collocations. The purpose of our project was to obtain a more
flexible format for this dictionnary, the DiCo, which has a traditional structure. By compiling the DiCo,
we get an object model which, in turn, can be stored in an SQL database. We show how the object model
allows us to more easily access the data and gives us a new perspective on the structure of dictionary.
This latter can be completly reorganized following new axes like lexical function links.
1 Introduction
The present work is part of a lexicographic project that targets an electronic dictionary of French centered
on semantic derivations and collocations. The dictionary is developed within the framework of the Ex-
planatory Combinatorial Lexicology, the lexical module of the Meaning-Text Theory ((Mel’cˇuk, 1974),
(Žolkovskij & Mel’cˇuk, 1965), (Mel’cˇuk et al., 1995)) and the project is supervised by Igor Mel’cˇuk and
Alain Polguère at the OLST–Université de Montréal. The electronic dictionary, the DiCo, is designed to
serve as a generic lexicographic description from which one can produce i) "computable" databases such
as the one presented here and ii) "general public" descriptions such as the Lexique Actif du Français or
LAF (Polguère, 2000). The DiCo possesses a rather traditional structure, inspired by paper dictionaries,
and adopted by numerous electronic dictionaries (TLFi (Dendien & Pierrel, 2003), eEH (Arregi et al.,
2003)). The entries of the dictionary are vocables (including idioms). Every vocable is a set of lexical
units corresponding to its different senses. Our goal was to propose for the DiCo a richer and more
flexible architecture to improve the access to the data. On one hand, this architecture aims at improving
the query possibilities of the DiCo for human users and at making the lexicographic information exploi-
table by natural language processing systems (especially in natural language generation). On the other
hand, it should facilitate all the tasks of updating and development of the dictionary, that is the lexico-
graphic tasks. For that reason, we chose to parse the existing dictionary, the DiCo, and then to feed a
relational database via an object representation. In this paper, we present the result of this modeling, the
DiCobjet, and show the advantages of such a structure from a theoretical point of view as well as from
a practical one. This structuring can be compared with the one which is used in WordNet (Fellbaum,
1998). However, as we shall see, the network resulting from the analysis connects not only lexical items
by means of lexical function relations, but also encodes all lexicographic information that is associated
with each lexical unit (such as, for example, the subcategorization frame). We first introduce the DiCo as
it is developed by lexicographers, then we describe its compiled structure and its representation. We end
with a discussion of the theoretical and practical advantages obtained by our modelization.
Compiling an MTT dictionary into a database
2 Overview of the DiCo
As we said, the DiCo adopts a structure close to the structure of standard paper dictionaries, that is, a
structuring made up of lexicographic entries. This structuring is required by the lexicographer, who wants
to have a global vision of the bulk of information related to each lexical unit. The description inside an
entry consists of nine main fields, each corresponding to a specific type of information, as we can see on
Figure 1.
Field Value
word ENGUEULADE
lexicographic number 1
grammatical properties nom, fém, "fam"
semantic label communication langagière
semantic formula ˜ DE L’individu X [VISANT L’individu Y] POUR LE fait Z
subcategorization X = I = de N, A-poss
frame table Y = II = --
Z = III = Prep-pour N | Prep-pour = {_à propos de_, _au
sujet de_, pour}, pour V-inf-passé
synonymy {QSyn} "fam" savon; "soutenu" admonestation,
remontrance, réprimande; blâme
lexical functions {QAnti} compliment, félicitation; flâtterie
{V0} engueuler
{Magn} belle, bonne, sacrée | antepos < majeure |
postpos
{Oper213} essuyer [ART ˜ _de la part de_ N=X Prep-pour
N=Z]
{Oper23} subir [ART ˜ Prep-pour N=Z]
Phraselogy
FIG. 1 – Partial description of the lexical unit ENGUEULADE1 (=‘argument’, ‘bawling out’)
The first two fields contain the name of the vocable and the lexicographic number of the lexical unit. The
grammatical properties field records the part of speech of the lexical unit as well as other information
relative to its cooccurrence : stylistic label (ex : "fam"), graphic variants, inflection constraints (ex :
"no plural"), and so on. The semantic label field position the lexical unit in a semantic hierarchy used
to account for the central semantic behavior of lexical units (for a detailed description of the DiCo
semantic labeling, see (Polguère, 2003)). The semantic formula field enumerates the semantic actants
of the lexical item and possibly supplies them with a semantic label. The subcategorization frame
table describe how semantic actants are to be expressed in structures that are syntactically controled by
the lexical unit. Synonymy and Lexical Functions fields describe lexical function links controled by the
lexical unit. A lexical function’s name is written between braces and is followed by a value list. Lexical
functions like Magn or Operi allow to describe the collocations in which the lexical unit occurs : une
belle engueulade, une sacrée engueulade or subir une engueulade. Finally the phraseology field lists
all the full idioms that formally contain the lexical unit. It is empty here, ENGUEULADE1 having no
associated full idioms. In practice, a relational mono-table database is used for the storage of the DiCo.
Every entry is a record, each row corresponding to a field inside the record. Beyond this first level of
structuring, we find a second level of structuring, which is syntactic. Every field is written according
to some syntactic and typographic conventions. Thus, it becomes possible to identify automatically the
keys of the description. We were able to design a compiler to translate automatically the DiCo into the
DiCobjet. A similar work was made within the framework of the project Papillon for the translation of
the DiCo in a XML format ((Lapalme & Sérasset, 2003)).
Compiling an MTT dictionary into a database
3 Object Modeling of the DiCo
3.1 General overview of the object modeling
As we can see, the fields described in the previous section contain lists of information items which we
can split into fields and so on. This is the compiler purpose. The content of the DiCo is fed into the
compiler as a tab-separated text. The compiler parses the file and produces a semantic representation of
the DiCo, the DiCobjet1. One of the objectives that we set ourselves in compiling the DiCo was to obtain
the most detailed representation as possible. But in fact, the modeling only consists in bringing to light
(by clarifying it) the structure of the DiCo. So, by examining again figure 1, we notice that the lexical
function field contains a list of lexical functions. A lexical function is supplied with a value list linked to
the lexical function formula (for example, Oper213). Each of these values (a support verb in this case)
can be organized in turn in fields : the value itself, its style label ("soutenu"), its subcategorization
frame, a constraint (for example postpos for an adjective), and so on.
n a m e
S
e m a n t i c L a b e l F o r m u l a
n a m e
h
o m o n y m y N u m
p a r t O f
S
p e e c
h
i s R e f l e x i v e
W
o r d
t y p e
i d e n t i f i e r
L F F o r m u l a
n a m e
i s O p t i o n a l
S
e m A c t a n t V a r
D
i c o
l e x i c o g r a p
h
i c N u m
c o r r e c t n e s s
i s B a s e L U
n o t a B e n e
a u t
h
o r
d a t e
e x a m p l e s
r e m a r k s
L e x i c a l U n i t
S
u b C a t F r a m e
G
r a m P r o p
n a m e
a c t a n t s
L F P r i m i t i v e
n a m e
L F R u b r i c
n a m e
s t y l e L a b e l
P
h
r a s e m e
n u m b e r
c o n s t r a i n t
S
u b C a t F r a m e T a b l e
i d e n t i f i e r
v a l u e
G
l o s s
0 . . * 1
. . *
1
0 . . *
0 . . *
1
. . *
1
0 . . *
n a m e
n u m b e r
S
e m A c t a n t
n a m e
S
e m a n t i c L a b e l
n a m e
P r i m i t i v e L a b e l
p
h
r a s e
c o n s t r a i n t s
e x a m p l e s
S
u b C a t V a l u e
n a m e
S
y n t A c t a n t
n a m e
f a m i l y
p o s i t i o n
f u s i o n
s t y l e L a b e l
s u b C a t F r a m e
g r a d a t i o n
c o n s t r a i n t
e x a m p l e
L F V a l u e
L F
1
. . *
1
. . *
0 . .
1
1
1
. . *
1
. . *
1
0 . . *
1
. . *
0 . .
1 1
0 . . *
1
. . *
n a m e
G
r a m P r o p P r i m i t i v e
1
. . *
FIG. 2 – DiCo Object Diagram
The work of the compiler thus consists in identifying the atoms of information and organizing them in
an adequate data structure. The data structure representing the DiCo is the DiCobjet (see the diagram,
figure 2). We represented the classes (that is, the definition of objects) by boxes. The upper part of the
box is reserved for the name of the class. The lower part enumerates the attributes which are of primitive
type (integer, boolean, character strings). Other attributes, which have classes for value, are represented
by the relations between the classes. These relations, although directed, are bidirectional. We call them
aggregate relations. Such a relation means that the class being on the side of the diamond owns one or
several classes as attributes. On the other side of the relation, we wrote the number of objects expected
in the aggregation. Figure 2 must be read in the following way : a DiCobjet is a set (of size superior or
equal to 0) of Word objects. The Word class is characterized by attributes (only the attribute "name" being
compulsory) and a set of LexicalUnit objects (the set must include at least one element). A LexicalUnit
1Semantic representation is a computer science concept. From the computer point of view, the input is just a character
string. In compiling it, the character string is translated into objects which have a semantic value. For example, the input string
{Magn} becomes a LFFormula object (and therefore it has some specific properties).
Compiling an MTT dictionary into a database
is described in turn as a container of collections of complex objects : SemanticLabelFormula, a set of
semantic actants (SemActantVar), a set of tables of subcategorization frame (SubCatFrameTable), a set
of Phrasemes, one grammatical property (GramProp, which is a set of grammatical properties primes)
and LFRubric. LFRubric, besides being defined by a name, includes a set of objects of type LF, this last
class consisting of the grouping of LFFormulas (what we usually call a Lexical Function), of a Gloss (the
paraphrase in natural language of the lexical function) and of a set of LFValue (the values returned by the
lexical function applied to the described lexical unit). Finally, LFFormula is a tree structure combining
some LFPrimitive. The class LFValue contains many attributes. Among these, the value strictly speaking
(for example, flatterie) is a string. This modeling is not satisfactory as far as the value is in fact a more
complex object and might be treated as a LexicalUnit. In the case of a complex lexical item like an
expression, we give its syntactic composition with a dependency tree. We have to emphasize that the
aggregate relation does not foresee the orientation of the link between objects. If SubCatFrameTable is
clearly an attribute of a LexicalUnit, it is also possible to go back up from a given SubCatFrameTable
to the LexicalItem objects which possess it. In the conclusion we will return to the repercussions of this
property of the model on the conception we have of the dictionary.
3.2 Exploitation
The advantages of object modeling are numerous. It becomes possible to do sophisticated queries and
to filter the results of these to keep only the relevant information (instead of the complete records). For
example, we can retrieve the list of the lexical units having at least two actants whose first one is realized
by the surface forms de N, A-poss or the lexical items having at once two semantic actants and one
Real@. To allow this enhancement of the query power, it is necessary to add the possibility of making
queries under other viewpoints that the one imposed by the structuring in words. We can consider, for
example, the dictionary from the lexical functions point of view. The current version of the DiCo gives
143 different values for the lexical function Oper1 (Figure 3 gives a sample). We get back also 48
different lexical functions returning the value donner (see figure 4).
nb Valeur nb Valeur nb Valeur nb Valeur
64 avoir 14 pousser 1 aller 1 être pris
42 être 11 émettre 1 battre 1 jauger
27 faire 10 constituer 1 célébrer 1 occuper
20 posséder 9 _faire preuve_ 1 comprendre 1 partir
17 ressentir 8 se trouver 1 couvrir 1 peupler
15 éprouver (. . . ) (. . . ) 1 être (présent) 1 proférer
FIG. 3 – Oper1 values in decreasing frequency
nb FL nb FL nb FL
10 {CausFunc1} 3 {Liqu1Oper1} 2 {Labreal21}
7 {Oper12} 3 {Son} 2 {Liqu1Real1}
6 {Oper1} 2 {Caus1Func0} 2 {Real31–I}
5 {Oper2} 2 {Caus de nouveau Func1} 2 {Real31–II}
4 {Oper13} 2 {Caus1Func0} 2 {Realo–II}
4 {Real12} 2 {Fact1} 1 {PredAble2}
3 {Caus3Func0} 1 {Fact21-production} . . . . . .
FIG. 4 – Lexical Functions returning the lexical unit donner in the current version of the DiCo
So, as it was requested by ((Grossmann & Tutin, 2003)), we can now try to discover regularities among
the values since we can now group them by the semantic label of the lexical unit they are linked to. For
Compiling an MTT dictionary into a database
example, we can see that many lexical units labeled with the semantic label sentiment (feeling) have the
lexical function IncepPredPlus returning the value augmenter (to increase). Similarly, we can compare
values returned by the LF’s Oper1 and Real1 or Fact0 and Real1. It is also possible to check wether a
lexical unit is, at the same time, an argument of many LF’s such as Oper1 and Real12.
Further applications could possibly be the use of the DiCobjet API to program procedures of planification
for new entries based on related entries. Not only the trivial QSyn relation could be used, but also lexical
units sharing the same semantic label.
3.3 Practical and theoretical contribution of object modeling
The DiCobjet was automatically extracted from the DiCo. This was possible thanks to the usage of
strict conventions in the editing of the DiCo (only some minor adjustments were necessary to reduce
the existing ambiguities). Notice that one of the main requirements of the lexicographers is to be able to
continue to develop the DiCo with its initial format (or an equivalent one). Indeed, as we said earlier, the
compilation of a dictionary cannot amount to a blind filling of predefined fields and the lexicographer
must be able to read a dictionary entry taken as a whole. As is expected, the object modeling of the
dictionary increases the access to the data of the DiCo, by allowing varied queries. More crucially the
result returned by these queries is not any more inevitably the entry, it can be a value of lexical function
or a set of subcategorization frames. Besides the query and the exploitation, the modeling facilitates the
revision of the DiCo by enabling an easy check of the homogeneity of every type of information. It also
facilitates its development by the processing on the data and by allowing for example to combine the
information of several entries to build the skeleton of a new entry. The object modeling of the dictionary
increases not only the possibilities of data mining. The most important and least expected result from the
project is that our vision of the dictionary changed. For example, at the surface level, the dictionary is no
longer a flat collection of entries. The object model can be taken in fact by any end and the DiCo can thus
be completly turned upside down. We can get into the DiCo by the FL object and produce for every lexical
function an entry giving the lists of the values for every keyword. We have then a much more semantic
vision of the dictionary, where we see how senses like the intensification, the causation, the realization,
etc. are realized in very different ways. We do not have to deal any more with a dictionary of 2000 entries
as in the beginning, but with a dictionary of several dozens thousand entries. The online dictionary can
be reached at the following address : http ://www.olst.umontreal.ca/dicouebe/.
Références
ARREGI X., ARRIOLA J., ARTOLA X., DIAZ DE ILARRAZA A., GARCÍA E., V. L., SARASOLA K.,
SOROA A. & URIA L. (2003). Semiautomatic conversion of the euskal hitzegia basque dictionary to a
queryable electronic form. Traitement Automatique des langues, TAL, 44 n˚2, 107-124.
DENDIEN J. & PIERREL J. M. (2003). Le trésor de la langue française informatisé. un exemple
d’informatisation d’un dictionnaire de langue de référence. Traitement Automatique des langues, TAL,
44 n˚2, 11-37.
C. FELLBAUM, Ed. (1998). WordNet, An Electronic Lexical Database. MIT Press.
GROSSMANN F. & TUTIN A. (2003). Quelques pistes pour le traitement des collocations. In F.
GROSSMANN & A. TUTIN, Eds., Les collocations, analyse et traitements. Revue Française de linguis-
tique appliquée.
LAPALME G. & SÉRASSET G. (2003). Batch creation of Papillon entries from DiCo. In Workshop
Papillon.
MEL’ ˇCUK I. (1974). Opyt teorii lingvisticheskih modelej "smysl↔ tekst". semantika, sintaksis. Nauka.
2In the DiCo, 229 lexical units have Oper1 values while 99 have Real1 values ; but only 22 have both.
Compiling an MTT dictionary into a database
MEL’ ˇCUK I., CLAS A. & POLGUÈRE A. (1995). Introduction à la lexicologie explicative et combina-
toire. Duculot.
POLGUÈRE A. (2000). Towards a theoretically-motivated general public dictionary of semantic deriva-
tions and collocations for french. In Proceedings of EURALEX 2000.
POLGUÈRE A. (2003). Étiquetage sémantique des lexies du DiCo. Traitement Automatique des langues,
TAL, 44 n˚2.
ŽOLKOVSKIJ A. & MEL’ ˇCUK I. (1965). O vozmožnom metode i instrumentax semanticˇeskogo sinteza.
Naucˇno-texnicˇeskaja informacija, 6, 23–28.


English

Compiling a “classical” explanatory combinatorial lexicographic description into a relational database

Scientific Publications of the University of Toulouse II Le Mirail

Archive Ouverte a LUniversite Lyon 2

Name not available

https://halshs.archives-ouvertes.fr/halshs-00120390/file/dicouebe-mtt2005.pdf

Compiling a “classical” explanatory combinatorial lexicographic description into a relational database

Abstract

Similar works

Full text

Available Versions

Archive Ouverte en Sciences de l'Information et de la Communication

Scientific Publications of the University of Toulouse II Le Mirail

Archive Ouverte a LUniversite Lyon 2

Name not available