Nervo Verdezoto             University of Trento      nervo.verdezoto@studenti.unitn.it  Prof. Laure Vieu and Prof. Alessa...
Outline   Objectives and Tasks      – Data      – Ontological Principles      – Experiments      – Results   Manual Anal...
Objectives•   Get familiar with Ontology-driven    Conceptual Modeling•   Develop semi-automatic methods to    spot semant...
Tasks    Study WordNet semantic relations to spot ontological    problems    Applications:             RTE            ...
The Data      WordNet: 82115 synsets were examined to collect the initial data, 22187 were      involved in meronyms and ...
Ontological Principles•   Constraints: part and whole should be of a    similar nature.•   DOLCE-ontological distinctions ...
Experiments – Tests     [defining queries]•   Semantic Constraints     –    Test 0: Individual – Class pairs:             ...
Results                           Ontological Problems  180        163  160  140  120                                     ...
Manual Analysis and discussionGeneral Errors•       a synset is considered as a class but should be an individual    –    ...
Summary and future work•       An automatic query system based on ontological        principles and semantic constraints i...
THANK YOUNervo Verdezoto D.                     Master HLTI 2009-2010
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Application of formal ontology and semantic techniques to improve the coherence and usability of lexical resources

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WordNet is extensively used as a major lexical resource in NLP. However, its quality is far from perfect, and this alters the results of applications using it. We propose here to complement previous efforts for “cleaning up” the top level of its taxonomy with semi-automatic methods based on the detection of errors at the lower levels. The methods we propose test the coherence of two sources of knowledge, exploiting ontological principles and semantic constraints.

REFERENCE:
Nervo Verdezoto and Laure Vieu. ”Towards semi-automatic methods for improving WordNet”. In J.Bos and S. Pulman, editors, Proceedings of the Ninth International Conference on Computational Semantics (IWCS 2011) - Oxford, UK, January 2011, 275-284.

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Application of formal ontology and semantic techniques to improve the coherence and usability of lexical resources

  1. 1. Nervo Verdezoto University of Trento nervo.verdezoto@studenti.unitn.it Prof. Laure Vieu and Prof. Alessandro Oltramari TutorsApplication of formal ontology and semantic techniques to improve the coherence and usability of lexical resources Master HLTI 2009-2010
  2. 2. Outline Objectives and Tasks – Data – Ontological Principles – Experiments – Results Manual Analysis and discussion Summary Master HLTI 2009-2010
  3. 3. Objectives• Get familiar with Ontology-driven Conceptual Modeling• Develop semi-automatic methods to spot semantic/ontological problems in WordNet at lower levels• Get familiar with scientific reporting Master HLTI 2009-2010
  4. 4. Tasks Study WordNet semantic relations to spot ontological problems Applications:  RTE  Automatic detection of part-whole relations e.g. (atmospheric phenomenon, communication), (shape, artifact), (shape, physical phenomenon) Master HLTI 2009-2010
  5. 5. The Data WordNet: 82115 synsets were examined to collect the initial data, 22187 were involved in meronyms and holonyms relations (50% meronyms – 50% holonyms)  Semeval 2007: 89 pairs relations were extracted. Additionally, we eliminated the redundant pairs from initial data. MERONYMS 14000 12000 10000 8000 # PAIRS – MERONYMS 6000 4000 2000 0 MEMBER PART SUBSTANCE Master HLTI 2009-2010
  6. 6. Ontological Principles• Constraints: part and whole should be of a similar nature.• DOLCE-ontological distinctions between: – endurants (ED) or physical entities (like a dog, a table, a cave, etc.) – perdurants (PD) or eventualities (like a lecture, a sleep, a raining, etc.) – abstract (AB, entities like a number, the content of a text, etc.). Master HLTI 2009-2010
  7. 7. Experiments – Tests [defining queries]• Semantic Constraints – Test 0: Individual – Class pairs: • (great_divide%1:15:00,continental_divide%1:15:00) – Test 4: Meronymy – Member and Member–Collection pairs: • (coronal%1:06:00, rose%1:20:00)• Ontological Constraints – Test 1: ED–AB (test 1.1) or AB–ED (test 1.2) • Test 1.1: physical entity 1:03:00 (but not process 1:03:00) / abstraction 1:03:00 (but not event 1:03:00 + state 1:03:00. (head%1:06:04::,coin%1:21:02::) – Test 2: ED–PD (test 2.1) or PD–ED (test 2.2) • Test 2.1 , physical entity 1:03:00 (but not process 1:03:00) / process 1:03:00 + event 1:03:00 + state 1:03:00. ⟨air%1:27:00, wind%1:19:00⟩ – Test 3: PD–AB (test 3.1) or AB–PD (test 3.2) • Test 3.1 , abstraction 1:03:00 – but not event 1:03:00 + state 1:03:00(first all and then without group) / event 1:03:00 + state 1:03:00 + process 1:03:00. ⟨regulation time%1:28:00, athletic game%1:04:00⟩ Master HLTI 2009-2010
  8. 8. Results Ontological Problems 180 163 160 140 120 108 100 WORDNET SEMEVAL 80 60 45 40 20 2 2 0 Test 1 Test 2 Test 3 Ontological Problems 180 163 160 140 120 108 100 W ORDNET SEMEVAL 80 60 45 40 20 2 2 0 Test 1 Test 2 Test 3 Master HLTI 2009-2010
  9. 9. Manual Analysis and discussionGeneral Errors• a synset is considered as a class but should be an individual – Confusion between class and an instance of this class for which the term is used with a specific sense e.g., ⟨great_divide%1:15:00,continental_divide%1:15:00⟩ – Confusion between class and group e.g., new_testament%1:10:00• a synset is not attached to the right place in the taxonomy – Confusion between a property and a physical entity having that property (shape, quantity or measure, location) or between a relation and a physical entity being an argument in that relation e.g., coin%1:21:02, hay_mow%1:23:00 - calyx%1:20:00, mothball%1:06:00• a synset mixes two senses, and the missing sense should be attached elsewhere in the taxonomy or this missing sense is an individual, not a class – Confusion between 2 senses of a word, amounting to a missing sense e.g. ⟨ethiopian%1:18:00, ethiopia%1:15:00⟩• the meronymy relation is wrong – Confusion between meronymy and other relations (location, participation, etc.): • “is located in” - ⟨balkan_wars%1:04:00, balkan_peninsula%1:15:00⟩ • “participates in” - ⟨feminist%1:18:00,feminist_movement%1:04:00⟩ Master HLTI 2009-2010
  10. 10. Summary and future work• An automatic query system based on ontological principles and semantic constraints is effective to build semi-automatic methods to spot errors in WordNet• Increase the number and type of experiments• Exploit the results of this study to: – Develop a semi-automatic tool for ”cleaning-up” WordNet – Design and develop guidelines to help lexicographers (Christiane Fellbaum from Princeton WordNet Group) to prevent classical ontological mistakes – Evaluation for NLP applications Master HLTI 2009-2010
  11. 11. THANK YOUNervo Verdezoto D. Master HLTI 2009-2010

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