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Title: Formal analysis of concepts and onomasiological search of terms: towards new dictionaries


1
Formal analysis of concepts and onomasiological
search of terms towards new dictionaries
  • Amparo Alcina
  • TecnoLeTTr_at_
  • Universitat Jaume I de Castellón

TAMA Computational Terminology Workshop 9-10
October 2008
2
Index
  • Introduction
  • Translators and terminologists needs
  • Onomasiological dictionaries
  • ONTODIC
  • Aims
  • Context
  • Techniques
  • Applications

3
Introduction
4
Justification
  • Increase of specialized translation
  • Globalization
  • More specialized subjects
  • More terminological units and new concepts
  • Terminological needs for human and machine
    translation

Specialized texts
terminology
Translated texts
5
Translators needs
  • Translators use complex strategies that combine
  • Textual corpora and concordances
  • Texts in the Internet
  • Queries in definitions and other fields in
    electronic dictionaries
  • Comparison of definitions in monolingual
    dictionaries

6
Problem
  • Lack of terminological dictionaries
  • Current dictionaries offer semasiological
    inquiries
  • Fireman -gt Person who works candling fires.
  • But do not offer onomasiological inquiries
  • A lot of trees in a mountain -gt forest

7
manada cerdo piara
Herd pork herd2
8
By subject (science and technic)
9
Reverse dictionary, i.e. fire
http//dictionary.reference.com/reverse/
10
Problems for elaborating terminologies
  • Terminological databases -gt Limitations as
  • How to handle the branches of the subject tree
  • How to handle different kinds of concepts
    properties, relations, groups of terms
  • How to build terminological definitions
  • Production of definitions by hand -gt not
    efficient
  • Production of definitions by copy and paste -gt
    low quality

11
Three reasons for ONTODIC
  • Necessity of onomasiological search for
    translation purposes
  • Terminological databases do not offer concept
    management facilities
  • There is a lack of computer assisted terminology
    tools to support concept analysis

12
Aims and Techniques in ONTODIC
13
Context
  • Terminology Theory and terminography
  • Restricted domain
  • Only one or few senses for a term
  • Computational Linguistics and Knowledge
    Engineering
  • Ceramics terminology
  • Knowledge, documentation, experts

14
Phases
  • Conceptual description of terms
  • Formalize the conceptual analysis
  • Implement the conceptual analysis

15
Terminological description of concept terms
  • Each term must be assigned to a branch in the
    domain tree
  • Terms in a branch must be organized in concept
    groups
  • Each concept group must to share the same
    description template
  • Each description template contains
  • Concept class (descriptor)
  • Features of the term
  • Properties
  • Relationships

16
Ceramics domain tree
  • 1. Producto
  • 1.1 Producto acabado
  • Características del prod. Acabado
  • Defectos del prod. Acabado
  • Tipos de producto acabado
  • Partes del producto acabado
  • 1.2.Producto intermedio
  • Características del prod. intermedio
  • Defectos del prod. intermedio
  • Tipos de producto
  • 1.3. Otros productos
  • 2. Fabricación
  • Procesos
  • Maquinaria y accesorios
  • 3. Materias primas y aditivos
  • Materias primas
  • Aditivos
  • 4. Colocación
  • 4.1. Procesos de colocación
  • 4.2. Maquinaria y accesorios de colocación
  • 4.3. Materiales para colocación
  • 4.3.1. Materiales de base
  • 4.3.2. Materiales de adherencia
  • 5. Calidad
  • 5.1. Procesos de control de calidad
  • 5.2. Maquinaria y accesorios de control de
    calidad
  • 6. Unidades de medida
  • 7. Organismos, Instituciones

17
Concept groups Manufacture
production
Prensado explosivo
distribution
paletización
empaquetamiento
Prensado isostático
preparation
amasado
atomización
18
Analysis of terminological concepts
  • Term
  • Subject
  • Branch
  • Concept group
  • Descriptor
  • Characteristics

19
Exemple of terminological concept description in
normal database
  • Term tamizado
  • Subject cerámica
  • Branch Fabricación
  • Concept group proceso de preparación
  • Descriptor proceso de preparación
  • Characteristics
  • el material pasa a través de un tamiz que
    retiene los elementos más gruesos

20
Relationships between terms
21
Clasify elements of description
  • el material pasa a través de un tamiz que
    retiene los elementos más gruesos
  • The material go through a sieve that retains
    the large elements
  • Patient the material
  • Action go through a sieve
  • Result retains the large elements

22
Generalize (not ad hoc)
  • Estabilishing a broad, high level classification
    of terms, for instance, a meta-ontology (Sager
    and Kageura 1995)
  • Establishing a broad classification of
    relationships in terminology with formal
    specifications (Maroto 2007)
  • Establishing a broad classification of properties
    of terms (Estellés 2006 based on Kageura)

23
Concept classes
  • Entities
  • Activities
  • Relations
  • Properties

24
Concept classes
  • Entities
  • products, machines, materials
  • Activities
  • production, preparation
  • Relations
  • part-whole, generic-species
  • Properties
  • product characteristics

25
Relation template
26
Exemple of relation description
27
Exemple of search
  • a (domain) R b (rango)
  • Which kinds of ceramic tiles are produced by
    prensado en seco?
  • a (ACTIVITY) R (process-product) b (ENTITY)
  • (Prensado en seco) process-product (ceramic tile)

28
Characteristic template
29
Exemple of Characteristic description
30
Implementing
  • Concept analysis tools
  • Terminology
  • CODE, COGNITERM (Meyer 1997)
  • OntoTerm (Faber)
  • CAOS
  • Knowledge Engineering
  • Ontology editors WebODE, OntoEdit, KAON, Protégé
  • Protégé
  • University of Standford
  • Free
  • Open
  • A lot of functions, plug-ins
  • XML, OWL
  • inquiries

31
Advantages of Protégé
  • Similarity to terminological elements
  • Domain tree
  • Hierarchical organization of terms
  • Relations
  • Characteristics
  • Inquiries

32
Problems
  • Many elements must be adapted to our needs
  • The structure should be useful not only for a
    subject area, but also for other subjects
  • We must also work with denominations, for
    instance, equivalences

33
Exemple of search
  • a (domain) R b (rango)
  • Which kinds of ceramic tiles (b) are produced by
    prensado en seco (a)?
  • a (ACTIVITY) R (process-product) b (ENTITY)
  • (Prensado en seco) produce (ceramic tile)

34
Example of implementation
35
Exemple of query
36
Example of implementation
37
Applications
  • Offer tools for lexicographers, terminologists
    and translators, developing the concept analysis
    in an easily manageable way
  • Offer tools and terminological resources for
    queries ussually made by translators
  • Offer resources for Natural Language Processing
    (NLP)

38
Muchas gracias por vuestra atención!
  • Amparo Alcina (alcina_at_trad.uji.es)
  • http//tecnolettra.uji.es
  • Universitat Jaume I
  • Spain
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