Difference between revisions of "Vulcan/SystemTarget"

Revision as of 03:55, 22 August 2013

This page describes the features in the first implementation of the system.

I/O

Input

Natural language sentences as input.

The system will handle propositions that correspond to three questions.

Q1: X is the best conductor of electricity. X = {Iron nail, wax crayon, plastic cup, rubber boat}
Q2: X causes leaves of a plant to become larger. X = {Growth, A repair, Germination, Decomposition}
Q3: X helps a fox find food. X = {A sense of smell, ...}

Output

Marginal inference probability for each proposition according to Tuffy.

Set of rules and axioms used (human-readable and MLN format). Note this is going to be hand generated in this iteration.

Debugging output that shows the set of axioms, rules and new facts used in the inference. Preferably in a graphical format.

Method

1. Hand generate the set of rules and axioms in a human-readable format (click [[|here]] for an example. 
   Convert this into the Tuffy MLN format. 
2. Run Open IE 4.0 on each input sentence. Extract the best tuple: One that covers the sentence best. 
   If there is a tie use the tuple with the longest relation phrase.
3. 

System Components