!7

p {
  ai_alternativeSmartBot();
  
  temp final ActualThoughtSpace ts = newThoughtSpace();
  ts.blockedB = litsymbolset("possibly related to:");
  
  doEvery_daemon(1000, new Runnable {
    int n = ts.size();
    public void run() {
      int _n = ts.size();
      if (_n != n)
        print("Thought space size: " + (n = _n));
    }
  });
  
  L<TripleWeb> blocked = thoughtSpace_allBlocked(ts);
  print("Blocked: " + l(blocked));
  
  //Collection<S> terms = allFullIndexedTerms();
  Set<S> terms = asSet(ai_texts("$X", "possibly related to:", "$Y", ts.parent));
  print("Scanning " + l(terms) + " terms of approx. " + ai_indexSize());
  
  for (S term : terms)
    ai_spec_allWords(term);
    
  print("Blocked: " + l(blocked) + ", recreated: " + ts.size());
  
  new L<TripleWeb> gained;
  new L<TripleWeb> ok;
  MultiMap<T3<Symbol>, TripleWeb> _blocked = triplesByContentMap(blocked);
  for (TripleWeb w : ts.allTriples()) {
    T3<Symbol> t = new Triple<Symbol>(w);
    if (_blocked.containsKey(t)) {
      ok.add(w);
      _blocked.remove(t);
    } else
      gained.add(w);
  }
  Collection<TripleWeb> lost = values(_blocked);
  
  print("Lost: " + nTriple(lost) + ", gained: " + nTriple(gained));
  
  printAsciiHeading("Lost Examples");
  pnl(takeFirst(10, lost));
  
  printAsciiHeading("Gained Examples");
  pnl(takeFirst(10, gained));
  
  printAsciiHeading("OK Examples (" + l(ok + ")");
  pnl(takeFirst(10, ok));
}