Enriching linguistic resources with domain information has been considered one important target in natural language applications. This domain information can be undoubtedly provided by subject specific definitions. However, definition extraction of this domain information from specialized resources has revealed certain methodological problems in definition construction. This paper presents some problems that are mainly related to inconsistencies in definitions. To face these problems some Meaning-Text Theory tools have been used: semantic labels, lexical functions and actantial structure as a solution for inferring domain knowledge and a way of providing coherence to definitions

Aguado de Cea, G.

Barrios, Maria

Ramos, José A.

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Semantic labels and genus: improving specialized domain definitions

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Ontology Engineering Group 
Laboratorio de Inteligencia Artificial 
Dept. Inteligencia Artificial, Facultad de Informática – UPM 
Campus de Montegancedo, s/n – Boadilla del Monte – 28660 Madrid Phone: +34 91 336 74 39 – Fax: +34 91 352 48 19 
 
 
 
 
 
OEG Publication 
 
 
 
 
 
 
 
 
 
Barrios MA, Ramos JA, Aguado de Cea G 
 
Semantic labels and genus: improving specialized domain definitions 
 
8th International Conference on Terminology and Artificial Intelligence (TIA09) 
November 18th-20th, 2009 
Toulouse, France. 
Pages: 6 
Presented as poster. 
 
 Semantic labels and genus: improving 
specialized domain definitions  
María A. Barrios, José A. Ramos and Guadalupe Aguado 
Ontology Engineering Group, Fac. Informática, Univ. Politécnica de Madrid  
Avda. Montepríncipe s/n, 28660 Boadilla del Monte, Spain 
mabarrios@delicias.dia.fi.upm.es;{jarg,lupe}@fi.upm.es 
Abstract: Enriching linguistic resources with domain information has been 
considered one important target in natural language applications. This domain 
information can be undoubtedly provided by subject specific definitions. 
However, definition extraction of this domain information from specialized 
resources has revealed certain methodological problems in definition 
construction. This paper presents some problems that are mainly related to 
inconsistencies in definitions. To face these problems some Meaning-Text 
Theory tools have been used: semantic labels, lexical functions and actantial 
structure as a solution for inferring domain knowledge and a way of providing 
coherence to definitions.  
Keywords: Definition extraction, linguistic resource enrichment, definition 
reuse, Meaning Text Theory. 
1 Introduction 
Specialized domain definitions have deserved the attention of many scholars from 
a wide range of fields, though with different purposes: terminology (Wüster, 
1979/1998; Sager, 1990; Cabré, 1992), specialized languages (Swales, 1985; Trimble, 
1985), corpus linguistics (Pearson, 1998), natural language processing (Malaisé et al., 
2005; Sierra et al., 2008) and standardization institutions (ISO/DIS 704, 2008; ISO 
1087-1, 2000). However, although definitions are of utmost importance nowadays in 
technical documentation, for example, when building an ontology, preparing a 
knowledge-based model or writing product or software specifications, to mention just 
a few, the problem of achieving a consensus on good practices in terminological 
definitions is far from being reached, even in standardized documents (Pozzi, 2000).  
Some of these definitional problems refer to inconsistencies in the same 
lexicographic work, such as term variants, use of different genus to define lexical 
units belonging to the same lexical field, etc. In this paper, we present a use case in 
which, taking three domain resources as basis for manual extracting definitions, 
consistency and sistematicity problems have appeared. The three domain definition 
resources used have been provided by the National Geographic Institute of Spain 
(IGN-E), and they correspond to several knowledge bases: the Concise Gazetteer 
TIA’09 
2 
(NC), the Numerical Cartographic Database (BCN25), and the National Topographic 
Database (BTN25).  
In an attempt to solve these problems, we have applied the Meaning-Text Theory 
(MTT) principles (Mel’čuk, 1996 & 1997) to propose some systematic solutions for 
defining specialized domain terminology to be used in a knowledge-based linguistic 
resource, BADELE.30001 (Barrios & Bernardos, 2007; Bernardos & Barrios, 2008) 
that follows the MTT principles. Our aim is to enrich BADELE.3000, which is a 
general purpose linguistic resource containing the 3,000 Spanish nouns more used in 
Spain, with domain terms in order to convert it into a highly exploitable flexible 
lexicographic resource. The resulting resource called simply BADELE can later be 
used in ontology development, ontology localization, multimedia tagging and other 
web semantic tasks.  
This paper describes briefly the main concepts of MTT that have been applied 
here and its lexicographic tools, and then deals with a use case and the solutions 
proposed to the problems that have been encountered. Finally, some conclusions and 
future work are also presented. 
2 MTT and its lexicographic tools 
As for the lexicographic tools applied to BADELE.3000, we have resorted to 
three concepts proposed by the Meaning-Text Theory (MTT).  
The first one is the lexical function (LF) (Mel’čuk, 1996): a LF associates a given 
lexical expression L (such as sound), which is the argument or keyword of F, with a 
set of lexical expressions – the value of F (such as loud, strong, heavy, deafening, 
etc.) – expressing a specific meaning associated with F (for instance, ‘intense’ for the 
examples just mentioned which correspond to the LF known as Magn).  
The second concept is the semantic label (Polguère, 2003): for our defining 
purposes, a semantic label is the equivalent to the genus in traditional definitions by 
genus and differentia. For instance, whale could be defined as a ‘sea mammal that 
breathes air through a hole at the top of its head and is hunted for meat and for other 
purposes, as a source of other materials’. The first part of this definition, ‘sea 
mammal’, the genus, is known in MTT approach as semantic label; the second part of 
this definition, the differentia, can be sometimes attached to some LFs. 
The third concept is the actant (Mel’čuk, 2004a, 2004b) and its derivate, the 
actantial structure. Actants correspond to beings or things that participate in the 
process expressed by a predicate: MTT approach considers that there is a sort of 
argument structure in all kinds of predicative words, which means that not only do the 
verbs have actants but also the adjectives, adverbs and the predicative nouns. The 
actantial structure reflects the syntactic expression of the actants, as shown in the 
                                                          
1 BAse de Datos del Español como Lengua Extranjera de los 3000 sustantivos más usados del español de 
España (Database of Spanish as a Foreign Language which contains the 3.000 Spanish nouns more used in 
Spain) 
Semantic labels and genus: improving specialized domain definitions 
3 
example of fleuve (river) of Dicouèbe2: QUI COMMENCE AU lieu X, PASSE PAR 
LES lieux Z ET SE TERMINE DANS L’étendue d’eau Y (WHICH STARTS AT 
THE X place, FLOWS THROUGH THE Z places AND FINISHES AT THE Y area). 
3 Enriching BADELE: problems and solutions  
When we decided to reuse and enrich BADELE.3000 with subject domain 
knowledge we assumed that for our goal (defining terms) we could follow the same 
criteria that had been adopted when defining common nouns in that linguistic 
resource. However, the systematic criteria followed in BADELE.3000 were not 
present in the definitions of the geographical domain resources. The biggest problem 
found when reusing technical definitions proposed by experts was the lack of 
coherence due to the fact that definitions were written following an intuitive way. 
This lack of methodology in the knowledge sources implies inconsistencies in the 
definitions of terms belonging to the same lexical field; for instance, autonomous 
region and province were defined by experts as ‘administrative unit’, whereas 
municipality (in the same lexical field) was defined as ‘a set of people and the 
territory where they live’. 
So, in order to achieve coherence in the global set of definitions of the database, 
we resorted mainly to one of the MTT tools, the semantic label. Thus, we created one 
semantic label for every set of terms attached to the same semantic field (for instance, 
municipality, autonomous region and province were labeled as ‘administrative unit’).  
These semantic labels helped to “normalize” the definitions proposed by experts, 
which have to be included in BADELE.  
Then, we define the actantial structure of this semantic label: every 
‘administrative unit’ has a group of other administrative units or people who live at 
this administrative unit under a potential specific government (‘administrative unit’ 
grouping a set of X governed by Y). Following this criteria, we redefine all these 
terms. Only the term comarca (region) was recognized as a specific ‘administrative 
unit’ which is a natural division of territory and has not a specific government.  
We found many other cases of different genus in the definitions of terms 
belonging to the same lexical field, sometimes attached to the fact that the 
superordinate concept is not clear or that is not related to one specific lexical 
expression. For example, a yard is defined as a ‘construction’, whereas a dovecot is 
defined as a ‘building’, a silo as a ‘container’ and a tenting arena as a ‘yard’, as Table 
1 shows. 
 
Table 1 Variability in genus 
Term Definition 
corral 
(yard) 
Construcción o pequeña estructura más o menos estable, creada especialmente 
para cobijarse los pastores o recoger el ganado (Constructed area, more or 
                                                          
2 Dictionnaire en Ligne de Combinatoire du Français, developed within the MTT framework and 
accessible via web by http://olst.ling.umontreal.ca/dicouebe/ 
TIA’09 
4 
Term Definition 
less permanent, for shepherds or cattle) 
palomar 
(dovecot) 
Edificio donde se recogen y crían palomas (Building for sheltering and 
breeding doves) 
silo 
(silo) 
Recipiente cubierto destinado al almacenaje de productos sólidos (grano, 
forraje, áridos, etc.) (Container used for storing solid products (such as grain, 
fodder, sand, etc.) 
tentadero 
(tenting arena) 
Corral o sitio cerrado donde se realiza la tienta de los becerros para 
comprobar su bravura (Yard or enclosed place where bull calves are tested for 
their bravery) 
 
Thus, we made use of the semantic label to solve this problem and in a first phase 
we used ‘industrial installation’ (see Barrios, Aguado and Ramos, 2009). However, in 
our linguistic resource, BADELE.3000, we found yard and dovecot, defined (as 
general terms) as ‘animal sheltering’, that is understood as ‘construction where (an) 
animal(s) (of the same or similar species) live(s)’. The question that arose was: should 
we maintain this semantic label? When looking for an answer to this question we 
referred to lexical functions (LF) and found the LF S1, which is the name of the first 
actant of a word. Then we listed all the nouns that are related to this LF whose value 
is the noun denoting a type of animal, and found nine cases, listed in Table 2. 
 
Table 2 Values of Lexical Function S1 
Noun S1
jaula (cage) S1(jaula) = pájaro [S1(cage) = bird] 
establo (stable) S1(establo) = ganado (toro, caballo, oveja, cabra, cerdo) 
[S1(stable) = cattle (bull, horse,  sheep, goat, pig)] 
corral (yard) S1(corral) = ganado, gallina, conejo [S1(yard) = cattle, hen, rabbit] 
pocilga (pigsty) S1(pocilga) = cerdo [S1(pigsty) = pig] 
redil (fold) S1(redil) = ganado [S1(fold) = cattle] 
nido (nest) S1(nido) = ave [S1(nest) = bird] 
caseta de perro 
(kennel) 
S1(caseta de perro) = perro [S1(kennel) = dog] 
cuadra (stable) S1(cuadra) = caballo [S1(stable) = horse] 
palomar (dovecot) S1(palomar) = paloma [S1(dovecot) = pigeon] 
 
This lexical relation proves enough consistency to explain why all the nouns of 
the first column are labeled in our linguistic resource as ‘animal sheltering’. Then we 
decided to maintain this semantic label for yard and dovecot, considering that it helps 
to achieve more coherence for the set of entries of our resource. 
What should we do in other cases whose relations are not so clear such as silo and 
testing arena? The first term is not related to any noun denoting an animal-type by S1, 
and the second one, even if related to cattle it is not a place where cattle live. Yard 
(and other nouns of the same lexical field) was defined by experts as ‘construction’. 
This word (construction) was considered in our resource as a semantic label, with the 
Semantic labels and genus: improving specialized domain definitions 
5 
meaning of ‘something constructed for any concrete activity or purpose and usually 
placed in a specific location’. Then we realized that the LF Hiper (that is, the 
hypernym) relates ‘animal sheltering’ to its hypernym ‘construction’, and uses the 
semantic label ‘construction’ for silo and testing arena, which were added to our 
resource, thus sharing the semantic label with other general terms. Consequently, the 
definitions were modified before including them in our resource, as shown in Table 3. 
 
Table 3 Our proposal 
Term Definition Semantic Label 
corral 
(yard) 
Habitáculo de animal para el ganado 
(Animal sheltering for cattle) 
‘Animal 
sheltering’ 
palomar 
(dovecot) 
Habitáculo de animal para palomas (Animal sheltering for 
doves) 
‘Animal 
sheltering’ 
silo 
(silo) 
Construcción destinada al almacenaje de productos sólidos 
(grano, forraje, áridos, etc.) (Construction for storing solid 
products, such as grain, fodder, sand, etc.) 
‘Construction’ 
tentadero 
(tenting arena) 
Construcción en la que se realiza la tienta de los becerros 
para comprobar su bravura (Construction where bull calves 
are tested for their bravery) 
‘Construction’ 
4 Conclusions  
We have expanded and enriched the linguistic resource BADELE.3000, which 
contains the most used 3000 Spanish words, with 350 terms of the Geographic 
Phenomena domain. These terms were defined by experts and reused in order to 
improve a lexicographic resource, called simply BADELE, a database with more 
specific domain information and more comprehensive in comparison to 
BADELE.3000.  
The definitions proposed by experts were very useful, although we found some 
problems, most of them derived from formal inconsistencies. In order to solve them 
we propose the use of MTT tools. When we found inconsistencies related to different 
genus in the definitions of terms belonging to the same lexical field, we used the 
semantic labels, the actantial structure and the complete set of lexical functions. By 
doing so, it enables to achieve a set of term definitions which are coherent not only 
with their own set of terms, but also with the set of all the common nouns contained 
in our original linguistic resource. 
As our long-term goal is to obtain a linguistic resource which is as exploitable as 
possible, part of the future work will be dedicated to enrich BADELE with 
information of other domains. We can conclude that reusing definitions of terms 
proposed by experts is a good way to enrich a general linguistic resource, as long as 
all the formal inconsistencies are solved. The MTT tools have proved to be a valuable 
means by which to solve these problems. 
TIA’09 
6 
5 Acknowledgements 
This work has been partially funded by the National Project “GeoBuddies: 
Anotación semántica colaborativa con dispositivos móviles en el Camino de 
Santiago” (TSI 2007-65677 C02) and the European Project “NeOn” (FP6-027595). 
References 
BARRIOS M.A., AGUADO DE CEA, G., RAMOS J.A. (2009) Enriching a lexicographic tool with 
domain definitions: Problems and solutions. In Sierra et al (ed.) Proceedings of the 1st 
International Workshop on Definition Extraction. Incoma. Shoumen (Bulgaria), 14-20. 
BARRIOS M.A. & BERNARDOS M.S. (2007) BaDELE.3000: An implementation of the lexical 
inheritance principle. In GERDES et al, (eds.) Meaning-Text Theory 2007. Proceedings of the 
3nd International Conference on Meaning-Text Theory. Wiener Slawistischer Almanach. 
Sonderband, 69. 97-106. 
BERNARDOS M.S. & BARRIOS M.A. (2008) Data model for a lexical resource based on lexical 
functions. Research in Computing Science, vol. 27. 
CABRÉ M.T. (1992) La terminología. Barcelona: Empuríes. 
ISO/DIS 704 (2008) Terminology work — Principles and Methods. 
ISO 1087-1 (2000) Terminology work. Vocabulary: Theory & Application. 
ISO 1087-2 (2000) Terminology work. Computer Applications. 
ISO 19110 (2005) Geographic Information – Methodology for feature cataloguing. 
MALAISÉ V., ZWIEGENBAUM P & BACHIMONT B (2005) Mining defining contexts to help 
structuring differential ontologies. Terminology, 11(1), 21-54. 
MEL'ČUK I. (2004a/b). Actants in semantics and syntax I: Actants in semantics; Actants in 
semantics and syntax II: Actants in syntax. Linguistics, 42:1, 1-66; 42:2, 247-291. 
MEL’ČUK I. (1996) Lexical functions: A tool for the description of lexical relations in a lexicon. 
In WANNER, L. (ed.), Lexical functions in lexicography and natural language processing. 
Amsterdam/ Philadelphia. John Benjamin, 37-102. 
OGC (2003) OpenGIS Reference Model, Version 0.1.2, OGC Inc. Wayland, MA, USA. 
PEARSON J. (1998) Terms in Contexts. Amsterdam. Philadelphia: John Benjamins. 
POLGUERE A. (2003) Étiquetage sémantique des lexies dans la base de données DiCo. TAL. Vol 
44, nº 2/2003, 39-68. 
POZZI M. (2000) ISO 704 e ISO1087-1: Dos Normas del ISO/TC37 en conflicto. VII Simposio 
de RITERM. http://www.riterm.net/actes/7simposio/pozzi.htm 
SAGER J.C. (1990) Curso práctico sobre el procesamiento de la terminología. Madrid: 
Fundación Germán Sánchez Ruipérez. 
SIERRA G., ALARCÓN R., AGUILAR C. & BACH C. (2008) Definitional verbal patterns for 
semantic relation extraction. Terminology, 14(1), 74-98 
SWALES J. (ed.) (1985) Episodes in ESP. Oxford: Pergamon Press. 
TRIMBLE L. (1985) English for Science and Technology: A Discourse Approach. Cambridge: 
CUP. 
WÜSTER E. (1979[1998]) Introducción a la teoría general de la terminología y a la 
lexicografía terminológica. Institut Universitari de Lingüística Aplicada. Universitat Pompeu 
Fabra. 


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