context: What intractability means in practice is open to debate. Saying that a problem is not in P does not imply that all large cases of the problem are hard or even that most of them are. For example, the decision problem in Presburger arithmetic has been shown not to be in P, yet algorithms have been written that solve the problem in reasonable times in most cases. Similarly, algorithms can solve the NP-complete knapsack problem over a wide range of sizes in less than quadratic time and SAT solvers routinely handle large instances of the NP-complete Boolean satisfiability problem.
question: How quickly can an algorithm solve an NP-complete knapsack problem?
answers: in less than quadratic time less than quadratic time less than quadratic time
content_span_normalized_text: similarly, algorithms can solve the np-complete knapsack problem over a wide range of sizes in less than quadratic time and sat solvers routinely handle large instances of the np-complete boolean satisfiability problem.
question_normalized_text: how quickly can an algorithm solve an np-complete knapsack problem?
context_asr: WHAT INTRACTABILITY MEANS IN PRACTISE IS OPEN TO DEBATE SEEING THAT A PROBLEM IS NOT IN PE DOES NOT IMPLY THAT ALL LARGE CASES OF THE PROBLEM ARE HARD OR EVEN THAT MOST OF THEM ARE FOR EXAMPLE THE DECISION PROBLEM IN PRISBURGER ARITHMETIC HAS BEEN SHOWN NOT TO BE IN PE YET ALGRITHEMS HAVE BEEN WRITTEN THAT SOLVED THE PROBLEM IN REASONABLE TIMES IN MOST CASES SIMILARLY ALGARITHEMS CAN SALVE THE ENPE COMPLETE NAPSACK PROBLEM OVER A WIDE RANGE OF SIZES IN LESS THAN QUADRATIC TIME AND SAT SALVERS ROUTINELY HANDLE LARGE INSTANCES OF THE ENPE COMPLETE BLING SATISFIABILITY PROBLEM 
question_asr: HOW QUICKLY CAN AN ALGARITOM SOLVE AN EN PE COMPLETE NAPSACK PROBLEM 