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  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>ISO</journal-title>
      </journal-title-group>
    </journal-meta>
    <article-meta>
      <title-group>
        <article-title>Semantic labels and genus: improving specialized domain definitions</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>María A. Barrios</string-name>
          <email>mabarrios@delicias.dia.fi.upm.es</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>José A. Ramos</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Guadalupe Aguado</string-name>
          <email>lupe@fi.upm.es</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Ontology Engineering Group</institution>
          ,
          <addr-line>Fac. Informática, Univ. Politécnica de Madrid Avda. Montepríncipe s/n, 28660 Boadilla del Monte</addr-line>
          ,
          <country country="ES">Spain</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>1992</year>
      </pub-date>
      <volume>1</volume>
      <issue>2000</issue>
      <abstract>
        <p>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.</p>
      </abstract>
      <kwd-group>
        <kwd>Definition extraction</kwd>
        <kwd>linguistic resource enrichment</kwd>
        <kwd>definition reuse</kwd>
        <kwd>Meaning Text Theory</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>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).</p>
      <p>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
(NC), the Numerical Cartographic Database (BCN25), and the National Topographic
Database (BTN25).</p>
      <p>In an attempt to solve these problems, we have applied the Meaning-Text Theory
(MTT) principles (Mel’čuk, 1996 &amp; 1997) to propose some systematic solutions for
defining specialized domain terminology to be used in a knowledge-based linguistic
resource, BADELE.30001 (Barrios &amp; Bernardos, 2007; Bernardos &amp; 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.</p>
      <p>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</p>
    </sec>
    <sec id="sec-2">
      <title>MTT and its lexicographic tools</title>
      <p>As for the lexicographic tools applied to BADELE.3000, we have resorted to
three concepts proposed by the Meaning-Text Theory (MTT).</p>
      <p>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).</p>
      <p>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.</p>
      <p>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)
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</p>
    </sec>
    <sec id="sec-3">
      <title>Enriching BADELE: problems and solutions</title>
      <p>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’.</p>
      <p>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.</p>
      <p>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.</p>
      <p>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.</p>
      <p>Term
corral
(yard)</p>
      <p>Term
palomar
(dovecot)
silo
(silo)</p>
      <p>Definition
less permanent, for shepherds or cattle)
Edificio donde se recogen y crían palomas (Building for sheltering and
breeding doves)
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 Corral o sitio cerrado donde se realiza la tienta de los becerros para
(tenting arena) comprobar su bravura (Yard or enclosed place where bull calves are tested for
their bravery)</p>
      <p>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.</p>
      <p>Noun
jaula (cage)
establo (stable)
corral (yard)
pocilga (pigsty)
redil (fold)
nido (nest)
caseta de perro
(kennel)
cuadra (stable)</p>
      <p>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.</p>
      <p>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
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.
corral Habitáculo de animal para el ganado
(yard) (Animal sheltering for cattle)
palomar Habitáculo de animal para palomas (Animal sheltering for
(dovecot) doves)
silo Construcción destinada al almacenaje de productos sólidos
(silo) (grano, forraje, áridos, etc.) (Construction for storing solid</p>
      <p>products, such as grain, fodder, sand, etc.)
tentadero Construcción en la que se realiza la tienta de los becerros
(tenting arena) para comprobar su bravura (Construction where bull calves
are tested for their bravery)</p>
      <p>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.</p>
      <p>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.</p>
      <p>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.
5</p>
    </sec>
    <sec id="sec-4">
      <title>Acknowledgements</title>
      <p>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).
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. &amp; 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.</p>
      <p>BERNARDOS M.S. &amp; BARRIOS M.A. (2008) Data model for a lexical resource based on lexical
functions. Research in Computing Science, vol. 27.</p>
      <p>ISO/DIS 704 (2008) Terminology work — Principles and Methods.
MALAISÉ V., ZWIEGENBAUM P &amp; BACHIMONT B (2005) Mining defining contexts to help
structuring differential ontologies. Terminology, 11(1), 21-54.</p>
      <p>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.
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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.</p>
      <p>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.</p>
      <p>SIERRA G., ALARCÓN R., AGUILAR C. &amp; 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.</p>
      <p>TRIMBLE L. (1985) English for Science and Technology: A Discourse Approach. Cambridge:
CUP.</p>
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