User's Guide of NAL

Input/Output Language

In this demonstration, NAL implements the following formal language, Narsese. The input and output of the system are Narsese judgments.
           <judgment> ::= [<statement> [frequency-value, confidence-value]]
          <statement> ::= <relation>(<term>, <term>)
                        | <compound-statement>
                        | <term>
               <term> ::= <word>
                        | <variable>
                        | <compound-term>
                        | <statement>
           <variable> ::= <independent-variable>
                        | <dependent-variable>(<independent-variable>*)
           <relation> ::= inheritance
                        | similarity
                        | implication
                        | equivalence
                        | instance
                        | property
                        | inst_prop                                // instance-property
 <compound-statement> ::= negation(<statement>)
                        | conjunction([<statement>, <statement>+]) 
                        | disjunction([<statement>, <statement>+]) 
      <compound-term> ::= ext_set([<term>+])                       // extensional set
                        | int_set([<term>+])                       // intensional set
                        | ext_intersection([<term>, <term>+])      // extensional intersection
                        | int_intersection([<term>, <term>+])      // intensional intersection
                        | ext_difference(<term>, <term>)           // extensional difference
                        | int_difference(<term>, <term>)           // intensional difference
                        | product([<term>, <term>+])
                        | ext_image(<term>, <term>)                // extensional image
                        | int_image(<term>, <term>)                // intensional image
The frequency-value is a real number in [0, 1]; the confidence-value a real number in (0, 1).

User Interface

The program can be invoked in the following ways: