1. Universiteit Twente Juggling Word Graphs A method for modeling the meaning of sentences using extended knowledge graphs.

2. Overview Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results, conclusions, future work ICCS ’02, Borovets

3. Introduction Parlevink: Computer Sciences Computational Language Dialogue systems in virtual environments Faculty of mathematics: Knowledge Graphs Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions University of Twente

4. Introduction Knowledge Graphs: Theoretical work on models of semantics and their mathematical properties, prof. Hoede et al. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions

5. Introduction No linguistics No concrete applications No automatic procedures Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions

6. Introduction Project: Building a system for automatic processing of Knowledge Graphs in a NLP environment. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions

7. Knowledge Graphs Reminder the intensional triangle Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Intension house man Ext() Extension Language Intensional semantics Extensional semantics

8. Knowledge Graphs Relations: Abstractions over human thinking Low level: no overlap, not divisible Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions

9. Knowledge Graphs Link weights describe the relevance of an aspect for: Determining extension of a concept Comparing concepts Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions

10. Knowledge Graphs Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions par COLOR ali par ali equ - equ par TIME ali CHANGING COLOR ord ANIMATE ALI CAU Example: painting as “causing a change of color”

11. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Processing Language S NP VP V Grammar Lexicon Parsing

12. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Processing Language “The man breaks the glass” Syntactical Unification Word graphs Possible sentence graphs Semantical evaluation Semantical unification

13. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Syntactic Unification “The man breaks the glass” Syntactical Unification Word graphs Possible sentence graphs Semantical evaluation Semantical unification

14. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Syntactic Unification par COLOR ali par ali equ - equ par TIME ali CHANGING COLOR ord ANIMATE ALI CAU “The man paints the wall” HUMAN ALI MALE ADULT

15. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Syntactic Unification Role node: a node in a graph serving as a connection point for other word graphs with a certain grammatical function.

16. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Syntactic Unification Role nodes are only syntactic Subject, object, head

17. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Syntactic Unification Semantical relationships stem from the place of a role node within the graph structure No roles for agent, location, instrument

18. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Semantic Evaluation “The man breaks the glass” Syntactical Unification Word graphs Possible sentence graphs Semantical evaluation Semantical unification

19. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Semantic Evaluation A LIVING ENTITY ali PERSON ali SELFCONCIOUS par “kill”“Oswald” Example: “The president kills Oswald”

20. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Semantic Evaluation A LIVING ENTITY ali PERSON ali SELFCONCIOUS par “kill”“Oswald” ali

21. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Semantic Evaluation A LIVING ENTITY ali PERSON ali SELFCONCIOUS par “kill”“Oswald” ali

22. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Semantic Evaluation POSPAR BREAK HUMAN ALI PAR MALE ADULT PAR 1 LIVING ENTITY ALI CAU 3 BROKEN PAR FRAGILE PAR 2 -PAR GLASS ALI PAR FRAGILE TRANSPARANT PAR BEVERAGE SUB EQU STONE ALI -PAR FRAGILE FPAR

23. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Semantic Evaluation POSPAR BREAK HUMAN ALIPAR MALEADULT PAR 1 LIVING ENTITY ALI CAU 3 BROKEN PAR FRAGILE PAR 2 -PAR GLASS ALI PAR FRAGILE TRANSPARANT PAR BEVERAGE SUB EQU STONE ALI -PAR FRAGILE SUB

24. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Semantic Unification “The man breaks the glass” Syntactical Unification Word graphs Possible sentence graphs Semantical evaluation Semantical unification

25. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Semantic Unification POSPAR BREAK HUMAN ALI PAR MALE ADULT PAR 1 LIVING ENTITY ALI CAU 3 BROKEN PAR FRAGILE PAR 2 -PAR GLASS ALI PAR FRAGILE TRANSPARANT PAR BEVERAGE SUB EQU STONE ALI -PAR FRAGILE FPAR CAU

26. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Results

27. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Results First tests: Small lexicon & grammar Ambiguities

28. Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Conclusions First results are good More testing needed Larger lexicon & grammar

29. Applications Ambiguity resolution in NLP systems Anaphor & coreference resolution Information Extraction Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions

30. Future Work Building a larger lexicon Automated lexicon learning Testing in dialog application (Virtual Music Centre) Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions

31. Questions & discussion