Balancing Lexicographic and Ontological Considerations in Ontology Development

Balancing Lexicographic and Ontological Considerations in

Ontology Development

First International Workshop on Ontological Analysis Trento, IT

16-20 July, 2012

Amanda Hicks, University at Buffalo

[email protected]

16-20 July, 2012 Balancing Lexicographic and Ontological Considerations

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Ontologies vs. Wordnets

Wordnets represent

• how we use language– the word ‘cat’ in context

Ontologies represent

• what it is to be a cat– e.g., whether being a cat is a rigid property


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Overview of some ontologies


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3 Layers of Ontologies

• Upper Most abstract

• Middle Intermediately abstract

• Domain Specific to a domain or

application


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Domain Ontologies

• are often developed by domain experts. • model highly specific, technical information.• often for use in a particular community of

researchers, technicians, etc. • Examples:

– Gene Ontology – KYOTO domain ontology– Protein Ontology


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Middle Ontologies

• are developed by ontologists or other information technologists.

• model concepts that are often part of a normal, spoken and written vocabulary and of an intermediate level of abstraction.

• connect upper-level ontologies with the domain ontology.

• Examples:– KYOTO Middle – Information Artifact Ontology


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Upper Ontologies

• developed by ontologists

• models highly abstract concepts– endurant vs. perdurant– quality vs. substance

• Because the axioms at this level will be inherited all the way down, we need to be really careful here!


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Upper Ontologies, some examples

BFO - http://www.ifomis.org/bfo

SUMO - http://www.ontologyportal.org

DOLCE http://www.loa.istc.cnr.it/DOLCE.html

http://www.ifomis.org/bfo

http://www.ontologyportal.org/

http://www.loa.istc.cnr.it/DOLCE.html


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BFO

• is a relatively shallow top ontology – 36 classes– 6 layers deep

• The BFO consortium coordinates many biomedical domain ontologies, users, and developers.


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DOLCE

• DOLCE-Lite– 37 classes– depth of 6

• DOLCE-Lite Plus– 208 classes– depth of 13


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The KYOTO Project

• 7th frame EU project, 2007-2010

• facilitates data mining and sharing from texts in the domain of ecology across seven languages

• WWF & ECNC are domain users

• www.kyoto-project.eu


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The KYOTO Ontology

• Three layers Top, Middle, Domain• Seven wordnets mapped to KYOTO Ontology

to facilitate data extraction and management– English– Spanish– Basque– Italian– Dutch– Japanese– Chinese


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The KYOTO Ontology

KYOTO 3 - three layers Top, Middle, Domain

Wordnets mapped to KYOTO Ontology to facilitate data extraction and sound inference– English– Spanish– Basque– Italian– Dutch– Japanese– Chinese

Use Protégé 4.0 or older. KYOTO is not written in OWL2.


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KYOTO Top

Based on DOLCE-Lite Plus• In DLP qualities are modeled according to the kinds

of entities that bear the quality.– e.g., size is a physical quality since it inheres in a physical

object

• KYOTO Top extends the physical-quality hierarchy– amount-of-matter-quality– feature-quality– physical-object-quality

• Added quality types– dispositional– relational


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KYOTO Top

KYOTO Top extends the role hierarchy.

Roles are arranged according to the kind of entity that bears that role.– A physical-object-role is played by a physical

object.– In the domain layer offspring is a subclass of

organism-role since organisms are the kinds of things that play the role of offspring.


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KYOTO Middle

Includes:• Base Concepts (BCs) from WordNet

– nouns• Units of measurement, e.g., length, and

other qualities• 72 new perdurants (processes and states)• 123 new endurant terms (objects and

substances)• qualities that model adjectives


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Base Concepts in KYOTO

Synsets from WordNet-3.0 (Fellbaum (1998))

– for each path from leaf to root: first node with at least 50 hyponyms

– roughly: cheap (and inadequate?) computational model for basic level concepts.

– CAREFUL: the set depends on structure and coverage of WordNet which is idosyncratic

• cake


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BCs facilitate mapping wordnets onto the ontology in KYOTO.

• WordNet is mapped onto the ontology via BCs.

• BC equivalents in other languages are indirectly mapped onto the ontology via mappings to WordNet’s BCs.


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• 297 BCs from the noun hierarchy and

• 578 BCs from the verb hierarchy– need work, in Domain layer– group names such as verb_change still

appear though not ontological(Izquierdo et al. (2007)).


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Sample BCs in KYOTO’s Middle Layer

• unit-of-measurement

• number

• color

• change

• book

• message

• food


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BCs and KYOTO

In this case, the lexicon in conjunction with considerations of the application informed the population of the Middle

and Domain layers of KYOTO.


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KYOTO Domain


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KYOTO Domain

Sample concepts from user scenarios– fish family– coast– soil– water– breed– biodiversity


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The Lexicon &

The Ontology


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is-a


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“is a” The Problem

“Is-a” is ambiguous between individuals and subclasses. This can lead to confusion.

For example, species terms can be confused.

Kermit is-ai leptopelis vermiculatus.

Leptopelis vermiculatus is-ac species.Therefore, Kermit is a species.


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“is-a”The Rule

The Rule: Every property of a class belongs to every instance of that class.

Check for all inherited properties.

Species are comprised of many organisms that can successfully reproduce fertile off-spring.

Is Kermit comprised of many organisms that can successfully reproduce fertile off-spring?


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“is a”KYOTO’s Solution

Model species terms twice!• Species in the sense of a group are modeled

as physical pluralities. This leptopelis vermiculatus is an instance NOT a subclass.

• ‘Leptopelis vermiculatus’ can also refer to a class. This is a type of organism.


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Rigid & Non-Rigid Terms


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Rigidity The Problem

In ontologies and WordNet the subsumption relations are determined according to different criteria.

• WordNet– Hypernymy– Based on psycholinguistic data; native language speakers

agree with word-use.

• Ontology – Subclass– Based on extention of a term, every x is a y.


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Transitivity of Subsumption

BECAREFUL! WordNet’s Hypernomy can lead to unsound inferences.

Conclusion: If every pet has an owner, then every cat has an owner.


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RigidityKYOTO’s Solution

• Distinguish rigid and non-rigid terms in the wordnet.– This distinction comes from OntoClean

(Guarino and Welty)

• Distinguish between roles and types in the ontology.

• Map synsets to the ontology using different mapping relations.


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Rigidity

• “Cat” is a rigid concept.

• “Pet” is a non-rigid concept.

• A concept is rigid if it is essential to all of its instances.– Permanence: Fluffy is always a cat, not

always a pet– Necessity: Fluffy cannot stop being a cat,

Fluffy can stop being a pet.


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The Rule of Thumb(See Giancarlo’s slides for a more nuanced view.)

Non-rigid terms should not subsume rigid terms.

or

Roles should not subsume types.


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A Jumbled Hierarchy

amount of matter-R drug

+R antibiotic+R chemical compound

+R oil-R nutriment (a source of material to nourish

the body)


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Clean Hierarchies

amount-of-matter

+R antibiotic+R chemical compound

+ R oil

substance-role (role played-by some amount-of matter)

-R drug-R nutriment


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Mapping Synsets


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Adjectives


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AdjectivesGeneral Strategy in KYOTOQualities are easily modeled according to the kinds of

entities in which they inhere.

For example, amounts of matter are the kinds of things that have pH levels.


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AdjectivesGeneral Strategy in KYOTOThe values for specific qualities like pH levels are

located in regions.


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AdjectivesThe Problem

pH-levels are easy because

• they are measureable, i.e., objective criteria.

• they are confined to one kind of entity, namely, amounts of matter.


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AdjectivesThe Problem

How should we model concepts like “beneficial” or “important”?

• Subjective component• Not necessarily “out there” in the world• Not typically quantifiable• Criteria are context dependent• Many kinds of entities can be beneficial

or important.


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AdjectivesKYOTO’s Solution

The middle layer has a region evaluative-region to accommodate adjectives like ‘beneficial’ or ‘worthless’.


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AdjectivesKYOTO’s Solution

Concepts like “beneficial” and “important” are

• not in the domain specific layer since they are general concepts.

• not in the upper layer since they are “subjective”.

• not in a strictly realist ontology like BFO.• modeled orthogonally to “real” qualities


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AdjectivesKYOTO’s solution

What kind of restriction can you write for length?

long or 2m.

Indefinite qualities

Definite qualities

length q-located-in (length-measurement-unit or indefinite-quality-region)


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In Conclusion

• Procurement - BCs influenced the concepts included in the KYOTO ontology.

• Hierarchy - subsumption relations must be carefully distinguished in order to avoid influence from the lexicon that might lead to unsound inferences

• Qualities - Lexicalized adjectives that may not have a realist corollary need to be modeled in an orthogonal way.


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BibliographyFellbaum, C., editor (1998). WordNet: An Electronic Lexical Database. The MIT Press.Guarino N., and Welty, C., (2004). An Overview of OntoClean, Handbook on

Ontologies, ed. S. Staab and R. Studer. pp. 151-172.Herold, A., Hicks, A., Rigau, G., & Laparra, E. (2009) Kyoto Deliverable D6.2: Central

Ontology Version - 1, www.kyoto-project.eu.Hicks, A., Rigau, G. (2010) Kyoto Deliverable D8.3: Domain Extension of the Central Ontology,

www.kyoto-project.eu. Izquierdo, R., Suárez, A., and Rigau, G. (2007). Exploring the automatic selection of basic level

concepts. In Proceedings of the International Conference on Recent Advances on Natural Language Processing (RANLP'07), Borovetz, Bulgaria.

Masolo, C., Borgo, S., Gangemi, A., Guarino, N., Oltramari, A., & Schneider, L. (2002). Wonderweb Deliverable D17. The Wonderweb Library of Foundational Ontologies and the Dolce Ontology.

Smith, B. (2004). Beyond Concepts: Ontology as Reality Representation. In Proccedings of FOIS 2004 International Conference on Formal Ontology and Information Systems.

Vossen P., et al. 2008. KYOTO: A system for Mining, Structuring and Distributing Knowledge Across Languages and Cultures. In Proceedings of LREC 2008, Marrakech, Morocco, May 28-30, 2008.

http://www.kyoto-project.eu/

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Balancing Lexicographic and Ontological Considerations in Ontology Development