a mini prolog interpreter on python

I used backword chaining in this porgram.
It could save space in memory, but it took a longer time for sentance query compared with forward chaining.
However, for any knowledge base smaller than 10k sentances (rules and facts), it should complete in less than 10 seconds.

• Achieved parsing and generated syntax tree by using Python Lex-Yacc module
• converted rules and fact into conjunctive normal form
• used an indexed-based knowledge base
• used backward chaining for sentence query
• avoided infinite loop in searching by implementing set of support