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KB Term:  Term intersection
English Word: 

Sigma KEE - increasesLikelihood
increasesLikelihood

appearance as argument number 1
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s__instance(s__increasesLikelihood,s__ProbabilityRelation)

Merge.kif 2702-2702 increases likelihood is an instance of probability relation
s__instance(s__increasesLikelihood,s__BinaryPredicate)

Merge.kif 2703-2703 increases likelihood is an instance of binary predicate
s__instance(s__increasesLikelihood,s__IrreflexiveRelation)

Merge.kif 2704-2704 increases likelihood is an instance of irreflexive relation
s__domain(s__increasesLikelihood,n__1,s__Formula)

Merge.kif 2705-2705 The number 1 argument of increases likelihood is an instance of formula
s__domain(s__increasesLikelihood,n__2,s__Formula)

Merge.kif 2706-2706 The number 2 argument of increases likelihood is an instance of formula
s__disjointRelation(s__increasesLikelihood,s__decreasesLikelihood)

Merge.kif 2707-2707 increases likelihood and decreases likelihood are disjoint
s__disjointRelation(s__increasesLikelihood,s__independentProbability)

Merge.kif 2708-2708 increases likelihood and independent probability are disjoint
s__documentation(s__increasesLikelihood, s__EnglishLanguage, "One of the basic ProbabilityRelations_ (increasesLikelihood ?FORMULA1 ?FORMULA2) means that ?FORMULA2 is more likely to be true if ?FORMULA1 is true_") Merge.kif 2711-2713 increases likelihood and independent probability are disjoint

appearance as argument number 2
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s__termFormat(s__EnglishLanguage, s__increasesLikelihood, "increases likelihood") domainEnglishFormat.kif 29547-29547
s__termFormat(s__ChineseTraditionalLanguage, s__increasesLikelihood, "增加可能性") domainEnglishFormat.kif 29548-29548
s__termFormat(s__ChineseLanguage, s__increasesLikelihood, "增加可能性") domainEnglishFormat.kif 29549-29549
s__format(s__EnglishLanguage, s__increasesLikelihood, "%1 %n{doesnt} increase%p{s} likelihood of %2") english_format.kif 126-126

antecedent
-------------------------


! [V__FORMULA1 : $i,V__FORMULA2 : $i,V__NUMBER1 : $real,V__NUMBER2 : $real] : (((s__increasesLikelihood(V__FORMULA1, V__FORMULA2) & s__ProbabilityFn(V__FORMULA2) = V__NUMBER1 & s__conditionalProbability(V__FORMULA1, V__FORMULA2, V__NUMBER2)) => ($greater(V__NUMBER2,V__NUMBER1)))) Merge.kif 2715-2720 If X increases likelihood of Y, equal the probability of Y and Z, and probability of X provided that Y holds is W, then W is greater than Z

consequent
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! [V__FORMULA1 : $i,V__FORMULA2 : $i] : (((s__instance(V__FORMULA1, s__Formula) & s__instance(V__FORMULA2, s__Formula)) => (s__increasesLikelihood(V__FORMULA1, V__FORMULA2) | s__decreasesLikelihood(V__FORMULA1, V__FORMULA2) | s__independentProbability(V__FORMULA1, V__FORMULA2)))) Merge.kif 2756-2763 If X is an instance of formula and Y is an instance of formula, then At least one of the following holds: (1) X increases likelihood of Y (2) X decreases likelihood of Y (3) probability of X and Y is independent
! [V__D : $i,V__S : $i] : ((s__pathologicSymptom(V__D, V__S) => ( ? [V__O:$i] : (s__increasesLikelihood(s__attribute(V__O, V__D), ( ? [V__I:$i] : ((s__instance(V__I, V__S) & s__experiencer(V__I, V__O))))))))) Merge.kif 10661-10669 If X is a symptom of Y, then there exists Z such that Y is an attribute of Z increases likelihood of there exists W such that W is an instance of X and Z experiences W
! [V__SV : $i] : ((s__instance(V__SV, s__SafetyVest) => s__hasPurpose(V__SV, ( ? [V__PERSON:$i, V__SPECTATOR:$i] : ((s__instance(V__PERSON, s__Animal) & s__instance(V__SPECTATOR, s__Human) & s__increasesLikelihood(s__wears(V__PERSON, V__SV), ( ? [V__SEE:$i] : ((s__instance(V__SEE, s__Seeing) & s__patient(V__SEE, V__PERSON) & s__experiencer(V__SEE, V__SPECTATOR))))) & s__decreasesLikelihood(( ? [V__SEE:$i] : ((s__instance(V__SEE, s__Seeing) & s__patient(V__SEE, V__PERSON) & s__experiencer(V__SEE, V__SPECTATOR)))), ( ? [V__INJ:$i] : ((s__instance(V__INJ, s__Injuring) & s__agent(V__INJ, V__SPECTATOR) & s__patient(V__INJ, V__PERSON))))))))))) Cars.kif 3422-3446 If X is an instance of safety vest, then All of the following hold: (1) X has the purpose there exist Y (2) Z such that Y is an instance of animal (3) Z is an instance of human (4) Y wears X increases likelihood of there exists W such that W is an instance of seeing (5) Y is a patient of W (6) Z experiences W (7) there exists W such that W is an instance of seeing (8) Y is a patient of W (9) Z experiences W decreases likelihood of there exists V such that V is an instance of injuring (10) Z is an agent of V (11) Y is a patient of V
! [V__CAR : $i,V__X : $i] : (((s__instance(V__X, s__CarAlarm) & s__instance(V__CAR, s__SelfPoweredRoadVehicle) & s__part(V__X, V__CAR)) => ( ? [V__HARM:$i, V__THIEF:$i, V__T:$i, V__L:$i] : (s__hasPurpose(V__X, (((s__instance(V__HARM, s__Stealing) | s__instance(V__HARM, s__Damaging)) & s__instance(V__THIEF, s__Human) & s__agent(V__HARM, V__THIEF) & s__patient(V__HARM, V__CAR) & s__WhenFn(V__HARM) = V__T & s__eventPartlyLocated(V__HARM, V__L)) => ( ? [V__ALARM:$i, V__WITNESS:$i] : ((s__instance(V__ALARM, s__RadiatingSound) & s__agent(V__ALARM, V__X) & s__causes(V__HARM, V__ALARM) & s__hasPurpose(V__ALARM, s__increasesLikelihood((s__instance(V__WITNESS, s__Human) & s__holdsDuring(V__T, s__orientation(V__WITNESS, V__L, s__Near))), (s__knows(V__WITNESS, ( ? [V__H:$i] : (((s__instance(V__H, s__Stealing) | s__instance(V__H, s__Damaging)) & s__eventPartlyLocated(V__H, V__L) & s__holdsDuring(V__T, s__patient(V__H, V__CAR)))))) | s__finishes(s__WhenFn(V__ALARM), s__WhenFn(V__HARM)))))))))))))) Cars.kif 3578-3618 If X is an instance of car alarm, Y is an instance of self powered road vehicle, and X is a part of Y, then All of the following hold: (1) there exist Z, W,, , V (2) U such that X has the purpose Z is an instance of stealing or Z is an instance of damaging (3) W is an instance of human (4) W is an agent of Z (5) Y is a patient of Z (6) equal the time of existence of Z (7) V (8) Z is partly located at Uthere exist T (9) S such that T is an instance of radiating sound (10) X is an agent of T (11) Z causes T (12) T has the purpose S is an instance of human (13) S is near to U holds during V increases likelihood of S knows there exists R such that R is an instance of stealing or R is an instance of damaging (14) R is partly located at U (15) Y is a patient of R holds during V or the time of existence of T finishes the time of existence of Z
! [V__DISEASE : $i,V__SYMPTOM : $i] : ((s__diseaseSymptom(V__DISEASE, V__SYMPTOM) => ( ? [V__ORGANISM:$i] : (s__increasesLikelihood(s__attribute(V__ORGANISM, V__DISEASE), s__attribute(V__ORGANISM, V__SYMPTOM)))))) WMD.kif 872-877 If X is a disease symptom of Y, then there exists Z such that Y is an attribute of Z increases likelihood of X is an attribute of Z
! [V__DISEASE : $i,V__PROCESS : $i,V__SUBSTANCE : $i] : ((s__diseaseMedicine(V__DISEASE, V__SUBSTANCE, V__PROCESS) => ( ? [V__ORGANISM:$i, V__TIME:$i, V__SAMPLE:$i, V__PROC:$i] : ((s__holdsDuring(V__TIME, s__attribute(V__ORGANISM, V__DISEASE)) & s__increasesLikelihood((s__instance(V__PROC, V__PROCESS) & s__temporalPart(s__WhenFn(V__PROC), V__TIME) & s__experiencer(V__PROC, V__ORGANISM) & s__patient(V__PROC, V__SAMPLE) & s__instance(V__SAMPLE, V__SUBSTANCE)), s__holdsDuring(s__ImmediateFutureFn(V__TIME), ~(s__attribute(V__ORGANISM, V__DISEASE))))))))) WMD.kif 936-951 If X is disease treatment Y for Z, then All of the following hold: (1) there exist W, V,, , U (2) T such that X is an attribute of W holds during V (3) T is an instance of Z (4) the time of existence of T is a part of V (5) W experiences T (6) U is a patient of T (7) U is an instance of Y increases likelihood of X is not an attribute of W holds during immediately after V

appearance as argument number 0
-------------------------


! [V__AGENT : $i,V__ORGANISM : $i,V__PROCESS : $i,V__PROCESSTYPE : $i,V__SYMPTOM : $i] : (s__increasesLikelihood((s__biochemicalAgentSyndrome(V__AGENT, V__SYMPTOM) & s__biochemicalAgentDelivery(V__AGENT, V__PROCESSTYPE) & s__instance(V__PROCESS, V__PROCESSTYPE) & s__experiencer(V__PROCESS, V__ORGANISM)), s__attribute(V__ORGANISM, V__SYMPTOM))) WMD.kif 762-768 ?SYMPTOM is a biochemical agent syndrome of ?AGENT, ?PROCESSTYPE is a biochemical agent delivery of ?AGENT, ?PROCESS is an instance of ?PROCESSTYPE, and ?ORGANISM experiences ?PROCESS increases likelihood of ?SYMPTOM is an attribute of ?ORGANISM


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