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< > BotCompany Repo | #1021251 // "Pizza with..." [sentence disambiguation logic engine demo, works]

JavaX source code (desktop) [tags: use-pretranspiled] - run with: x30.jar

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!7

sS data = [[

---- Rules

// Some reasonings that everybody will understand.
// Sorry for the curly braces, we have to help out the parser a tiny bit.
// First, the 3 different cases of what "pizza with..." can mean.

  I ate pizza with pepperoni.
  => {I ate pizza} and {the pizza had pepperoni on it}.
  
  I ate pizza with Bob.
  => {I ate pizza} and {Bob was with me}.
  
  I ate pizza with a fork.
  => I used a fork to eat pizza.
  
// Now some more easy rules.
  
  I used a fork to eat pizza.
  => I used a fork.
  
  I used a fork.
  => A fork is a tool.
  
  The pizza had pepperoni on it.
  => Pepperoni is edible.
  
  Bob was with me.
  => Bob is a person.

// Some VERY basic mathematical logic

  $A and $B.
  => $A.
  
  $A and $B.
  => $B.

// Tell the machine what is not plausible

  Mom is edible. => fail
  Mom is a tool. => fail
  anchovis are a tool. => fail
  anchovis are a person. => fail
  ducks are a tool. => fail
  ducks are a person. => fail
  my hands are edible. => fail
  my hands are a person. => fail

// That's it! Now for the input.

---- Input

  I ate pizza with mom.
  I ate pizza with anchovis.
  I ate pizza with ducks.
  I ate pizza with my hands.

]];

static int minScore = 50; // minimal percentage score for rule matching
sbool printMappings, printGroupedData, printRejectedVars;

static LPair<S> rules;
static Map<PairS, Set<S>> ruleVariables = new Map;

p-exp {
  centerBigTTConsole();
  
  S data = mapEachLine ai_groupSimplestNounPhrases(main.data);
  if (printGroupedData) print(data);
  SS sections = asCIMap(minusSignsSections(data));
  rules = ai_findDoubleArrowRulesAsPairs(sections.get("Rules"));
  for (PairS rule : rules)
    ruleVariables.put(rule, ai_wordsInBothSidesOfPair_uncurly(rule));

  printAsciiHeading("REASONING");
  new MultiMap<S> solutions;

  for (S input : tlft(sections.get("Input"))) {
    print("\nInput: " + tok_dropCurlyBrackets(input));
    temp tempIndent();
    for (Pair<S, Int> in : interpretations(input)) {
      print("\nInterpretation: " + formatForUser(in.a));
      Set<S> out = litciset();
      interpretRecursively(in.a, 5, out);
      if (!matchAny("fail", out))
        solutions.put(input, in.a);
    }
  }
  
  printAsciiHeading("RESULTS");
  print(formatDoubleArrowPairs_horizontallyAligned(mapPairBoth formatForUser(multiMapToPairs(solutions))));
}

svoid interpretRecursively(S input, int level, Set<S> out) {
  if (level <= 0) ret;
  LS interpretations = pairsA(interpretations(ai_groupSimplestNounPhrases(input)));
  temp tempIndent();
  for (S in : addAllAndReturnNew(out, interpretations)) {
    print(" => " + formatForUser(in));
    for (S s : lithashset(in, ai_superSimpleVerbCorrector(in)))
      interpretRecursively(s, level-1, out);
  }
}

static LS defaultParse(S s) {
  ret codeTokens_lazy_uncurly(javaTokWithBrackets_cached(s));
}

static LPair<S, Int> interpretations(S input) {
  LS tokI = defaultParse(input);
  //print("Raw parse: " + tokI);
  new LPair<S, Int> interpretations;
    
  for (PairS rule : rules) {
    LS tokR = defaultParse(rule.a);
    final SS map = ciMapWithoutKeysEqualToValues(zipTwoListsToCIMap_strict(tokR, tokI));
    if (map == null) continue;
    
    // Found matching rule
    
    int score = l(tokR)-l(map);
    L<S> nonVars = withoutDollarVars(listMinusSet(keys(map), ruleVariables.get(rule)));
    if (printRejectedVars && nempty(nonVars)) print("Rejected vars: " + nonVars);
    if (nempty(nonVars)) score = 0;
    if (printMappings) print("  " + reverseMapCI_joinDuplicatesWithPlus(map) + " | " + rule.a);
    
    // Make consequence
    
    S c = rule.b;
    c = join(mapCodeTokens(javaTok(c), func(S s) -> S { getOrKeep_tryUncurlied(map, s) }));
    c = join(mapCodeTokens(javaTokWithBrackets(c), func(S s) -> S { getOrKeep_tryUncurlied(map, s) }));
    //c = javaTokWithBrackets_recursiveTransform(func(S s) -> S { getOrKeep(map, s) }, c);
    
    addPairIfBAtLeast(interpretations, c, ratioToIntPercent(score, l(tokR)), minScore);
  }
    
  ret interpretations;
}

sS formatForUser(S s) {
  ret ai_superSimpleVerbCorrector(tok_dropCurlyBrackets(s));
}

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Snippet ID: #1021251
Snippet name: "Pizza with..." [sentence disambiguation logic engine demo, works]
Eternal ID of this version: #1021251/137
Text MD5: a3b2bb9ed62d3a03eb2dc6a203e77b41
Transpilation MD5: 218d438616b499619b081a5b88bf9b99
Author: stefan
Category: javax
Type: JavaX source code (desktop)
Public (visible to everyone): Yes
Archived (hidden from active list): No
Created/modified: 2019-02-07 16:50:54
Source code size: 4264 bytes / 147 lines
Pitched / IR pitched: No / No
Views / Downloads: 776 / 2715
Version history: 136 change(s)
Referenced in: [show references]