Symbolic/Subsymbolic Sentence Analysi: Exploiting the Best of Two Worlds
Wendy G. Lehnert · 1988
A NUMBER OF SEMANTICALLY-ORIENTED TECHNIQUES HAVE BEEN DEVISED OVER THE YEARS TO ADDRESS THE PROBLEMS OF CONCEPTUAL SENTENCE ANALYSIS. WE HAVE IMPLEMENTED A NATURAL LANGUAGE SENTENCE ANALYZER, `CIRCUS'', WHICH INCORPOR- ATES A NUMBER OF WELL-KNOWN TECHNIQUES FROM THE SYMBOLIC INFORMATION PRO- CESSING TRADITION ALONG WITH ORIGINAL TECHNIQUES BASED ON NUMERICAL RELAXA- TION. OUR BASIC SYSTEM ARCHITECTURE SUPPORTS A STACK-CONTROLLED MECHANISM FOR MANAGING SYNTACTIC PREDITIONS, AS WELL AS MODULES FOR HANDLING TWO FUNDAMENTALLY DISTINCT TYPES OF SEMANTIC PREFERENCES: PREDICTIVE SEMANTICS AND DATA-DRIVEN SEMANTICS. A MARKER PASSING ALGORITHM IS USED FOR PREDIC- TIVE SEMANTICS, AND NUMERICAL RELAXATION IS USED FOR DATA-DRIVEN SEMANTICS. THIS PAPER PROVIDES A GENERAL INTRODUCTION TO `CIRCUS'', THE OPPORTUNITIES FOR DIFFERENT KINDS OF MEMORY INTERACTIONS WITH `CIRCUS'', AND DETAILED (BUT NOT TECHNICAL) DESCRIPTIONS OF OUR MARKER PASSING AND NUMERICAL RELAXATION ALGORITHMS. `CIRCUS'' IS CURRENTLY RUNNING UNDER COMMON LISP ON THE TI EXPLORER.