Universiteit Twente Juggling Word Graphs A method for modeling the meaning of sentences using extended knowledge graphs.
Overview Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results, conclusions, future work ICCS ’02, Borovets
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
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
Introduction No linguistics No concrete applications No automatic procedures Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions
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
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
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
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
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”
Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Processing Language S NP VP V Grammar Lexicon Parsing
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
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
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
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.
Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Syntactic Unification Role nodes are only syntactic Subject, object, head
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
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
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”
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
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
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
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
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
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
Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Results
Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Results First tests: Small lexicon & grammar Ambiguities
Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions Conclusions First results are good More testing needed Larger lexicon & grammar
Applications Ambiguity resolution in NLP systems Anaphor & coreference resolution Information Extraction Introduction Knowledge Graphs Processing Language Syntactic unification Semantic evaluation Semantic unification Results & conclusions
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
Questions & discussion