nl premises stringlengths 41 1.12k | fol premises stringlengths 41 1.43k | nl conclusion stringlengths 12 378 | fol conclusion stringlengths 8 426 | label stringclasses 3
values |
|---|---|---|---|---|
No soccer players are professional basketball players.
All NBA players are professional basketball players.
All soccer defenders are soccer players.
All centerback players are soccer defenders.
If Stephen Curry is an NBA player or a soccer player, then he is a professional basketball player. | ∀x (ProfessionalSoccerPlayer(x) → ¬ProfessionalBasketballPlayer(x))
∀x (NBAPlayer(x) → ProfessionalBasketballPlayer(x))
∀x (ProfessionalSoccerDefender(x) → ProfessionalSoccerPlayer(x))
∀x (ProfessionalCenterback(x) → ProfessionalSoccerDefender(x))
(NBAPlayer(stephencurry) ⊕ ProfessionalSoccerPlayer(stephencurry)) → Pro... | Stephen Curry is an NBA player. | NBAPlayer(stephenCurry) | Uncertain |
No soccer players are professional basketball players.
All NBA players are professional basketball players.
All soccer defenders are soccer players.
All centerback players are soccer defenders.
If Stephen Curry is an NBA player or a soccer player, then he is a professional basketball player. | ∀x (ProfessionalSoccerPlayer(x) → ¬ProfessionalBasketballPlayer(x))
∀x (NBAPlayer(x) → ProfessionalBasketballPlayer(x))
∀x (ProfessionalSoccerDefender(x) → ProfessionalSoccerPlayer(x))
∀x (ProfessionalCenterback(x) → ProfessionalSoccerDefender(x))
(NBAPlayer(stephencurry) ⊕ ProfessionalSoccerPlayer(stephencurry)) → Pro... | Stephen Curry is a centerback player. | ProfessionalCenterback(stephenCurry) | False |
No soccer players are professional basketball players.
All NBA players are professional basketball players.
All soccer defenders are soccer players.
All centerback players are soccer defenders.
If Stephen Curry is an NBA player or a soccer player, then he is a professional basketball player. | ∀x (ProfessionalSoccerPlayer(x) → ¬ProfessionalBasketballPlayer(x))
∀x (NBAPlayer(x) → ProfessionalBasketballPlayer(x))
∀x (ProfessionalSoccerDefender(x) → ProfessionalSoccerPlayer(x))
∀x (ProfessionalCenterback(x) → ProfessionalSoccerDefender(x))
(NBAPlayer(stephencurry) ⊕ ProfessionalSoccerPlayer(stephencurry)) → Pro... | Stephen Curry is not a centerback player. | ¬ProfessionalCenterback(stephenCurry) | True |
No songs are visuals.
All folk songs are songs.
All videos are visuals.
All movies are videos.
All sci-fi movies are movies.
Inception is a sci-fi movie.
Mac is neither a folk song nor a sci-fi movie. | ∀x (Song(x) → ¬Visual(x))
∀x (FolkSong(x) → Song(x))
∀x (Video(x) → Visual(x))
∀x (Movie(x) → Video(x))
∀x (ScifiMovie(x) → Movie(x))
ScifiMovie(inception)
¬FolkSong(mac) ∧ ¬ScifiMovie(mac) | Inception is a folk song. | FolkSong(inception) | False |
No songs are visuals.
All folk songs are songs.
All videos are visuals.
All movies are videos.
All sci-fi movies are movies.
Inception is a sci-fi movie.
Mac is neither a folk song nor a sci-fi movie. | ∀x (Song(x) → ¬Visual(x))
∀x (FolkSong(x) → Song(x))
∀x (Video(x) → Visual(x))
∀x (Movie(x) → Video(x))
∀x (ScifiMovie(x) → Movie(x))
ScifiMovie(inception)
¬FolkSong(mac) ∧ ¬ScifiMovie(mac) | Inception is not a folk song. | ¬FolkSong(inception) | True |
No songs are visuals.
All folk songs are songs.
All videos are visuals.
All movies are videos.
All sci-fi movies are movies.
Inception is a sci-fi movie.
Mac is neither a folk song nor a sci-fi movie. | ∀x (Song(x) → ¬Visual(x))
∀x (FolkSong(x) → Song(x))
∀x (Video(x) → Visual(x))
∀x (Movie(x) → Video(x))
∀x (ScifiMovie(x) → Movie(x))
ScifiMovie(inception)
¬FolkSong(mac) ∧ ¬ScifiMovie(mac) | Inception is either a video or a folk song. | Video(inception) ⊕ FolkSong(inception) | True |
No songs are visuals.
All folk songs are songs.
All videos are visuals.
All movies are videos.
All sci-fi movies are movies.
Inception is a sci-fi movie.
Mac is neither a folk song nor a sci-fi movie. | ∀x (Song(x) → ¬Visual(x))
∀x (FolkSong(x) → Song(x))
∀x (Video(x) → Visual(x))
∀x (Movie(x) → Video(x))
∀x (ScifiMovie(x) → Movie(x))
ScifiMovie(inception)
¬FolkSong(mac) ∧ ¬ScifiMovie(mac) | Mac is a video. | Video(mac) | Uncertain |
All inductive reasoning processes derive general principles from a body of observations.
Two major types of reasoning rules are inductive reasoning and deductive reasoning.
All deductive reasoning processes are only based on facts and rules.
Nothing only based on facts and rules is used for statistical generalization... | ∀x (InductiveReasoning(x) → DeriveFrom(generalPrinciple, observations))
∀x (MajorArgumentForm(x) → (InductiveReasoning(x) ⊕ DeductiveReasoning(x)))
∀x (DeductiveReasoning(x) → (BasedOn(x, fact) ∨ BasedOn(x, rule)))
∀x ((BasedOn(x, fact) ∨ BasedOn(x, rule)) → (¬UsedFor(x, statisticalGeneralization)))
¬(InductiveReasonin... | Reasoning with Modus Ponens is based on facts and rules. | BasedOn(generalPrinciple, fact) ∨ BasedOn(generalPrinciple, rule) | Uncertain |
No trick-shot artist in Yale's varsity team struggles with half court shots.
Everyone on Yale's varsity team is someone who struggles with half court shots or who successfully shoots a high percentage of 3-pointers.
Everyone on Yale's varsity team who successfully shoots a high percentage of 3-pointers is solid at sh... | ∀x ((In(x, yaleSVarsityTeam) ∧ TrickShotArtist(x)) → ¬StruggleAt(x, halfCourtShot))
∀x (In(x, yaleSVarsityTeam) → (StruggleAt(x, halfCourtShot) ∨ GoodAt(x, threes)))
∀x ((In(x, yaleSVarsityTeam) ∧ GoodAt(x, threes)) → GoodAt(x, twos))
∀x ((In(x, yaleSVarsityTeam) ∧ GoodAt(x, twos)) → BadAt(x, midRangeShot))
In(jack, ya... | Jack struggles at half court shots. | StruggleAt(jack, halfCourtShot) | Uncertain |
No trick-shot artist in Yale's varsity team struggles with half court shots.
Everyone on Yale's varsity team is someone who struggles with half court shots or who successfully shoots a high percentage of 3-pointers.
Everyone on Yale's varsity team who successfully shoots a high percentage of 3-pointers is solid at sh... | ∀x ((In(x, yaleSVarsityTeam) ∧ TrickShotArtist(x)) → ¬StruggleAt(x, halfCourtShot))
∀x (In(x, yaleSVarsityTeam) → (StruggleAt(x, halfCourtShot) ∨ GoodAt(x, threes)))
∀x ((In(x, yaleSVarsityTeam) ∧ GoodAt(x, threes)) → GoodAt(x, twos))
∀x ((In(x, yaleSVarsityTeam) ∧ GoodAt(x, twos)) → BadAt(x, midRangeShot))
In(jack, ya... | Jack is solid at shooting 2-pointers or bad at mid-range shots. | GoodAt(jack, twos) ∨ BadAt(jack, midRangeShot) | True |
No trick-shot artist in Yale's varsity team struggles with half court shots.
Everyone on Yale's varsity team is someone who struggles with half court shots or who successfully shoots a high percentage of 3-pointers.
Everyone on Yale's varsity team who successfully shoots a high percentage of 3-pointers is solid at sh... | ∀x ((In(x, yaleSVarsityTeam) ∧ TrickShotArtist(x)) → ¬StruggleAt(x, halfCourtShot))
∀x (In(x, yaleSVarsityTeam) → (StruggleAt(x, halfCourtShot) ∨ GoodAt(x, threes)))
∀x ((In(x, yaleSVarsityTeam) ∧ GoodAt(x, threes)) → GoodAt(x, twos))
∀x ((In(x, yaleSVarsityTeam) ∧ GoodAt(x, twos)) → BadAt(x, midRangeShot))
In(jack, ya... | If Jack is not solid at shooting 2-pointers and bad at mid-range shots, then Jack is not solid at shooting 2-pointers and is a player who successfully shoots a high percentage of 3-pointers. | BadAt(jack, midRangeShot) ∧ GoodAt(jack, twos) → ¬GoodAt(jack, twos) ∧ GoodAt(jack, threes) | False |
No trick-shot artist in Yale's varsity team struggles with half court shots.
Everyone on Yale's varsity team is someone who struggles with half court shots or who successfully shoots a high percentage of 3-pointers.
Everyone on Yale's varsity team who successfully shoots a high percentage of 3-pointers is solid at sh... | ∀x ((In(x, yaleSVarsityTeam) ∧ TrickShotArtist(x)) → ¬StruggleAt(x, halfCourtShot))
∀x (In(x, yaleSVarsityTeam) → (StruggleAt(x, halfCourtShot) ∨ GoodAt(x, threes)))
∀x ((In(x, yaleSVarsityTeam) ∧ GoodAt(x, threes)) → GoodAt(x, twos))
∀x ((In(x, yaleSVarsityTeam) ∧ GoodAt(x, twos)) → BadAt(x, midRangeShot))
In(jack, ya... | If Jack is solid at shooting 2-pointers or successfully shoots a high percentage of 3-pointers, then Jack struggles at half court shots and is bad at mid-range shots. | GoodAt(jack, twos) ∨ GoodAt(jack, threes) → BadAt(jack, halfCourtShot) ∧ BadAt(jack, midRangeShot) | Uncertain |
No plants are fungi.
Mushrooms are fungi. | ∀x (Plant(x) → ¬Fungi(x))
∀x (Mushroom(x) → Fungi(x)) | No plants are mushrooms. | ∀x (Plant(x) → ¬Mushroom(x)) | True |
No road is dustless.
Some streets are roads. | ∀x (Road(x) → ¬Dustless(x))
∃x ∃y (Street(x) ∧ Street(y) ∧ Road(x) ∧ Road(y) ∧ ¬(x=y)) | Some streets are dustless. | ∃x ∃y (Street(x) ∧ Street(y) ∧ Dustless(x) ∧ Dustless(y) ∧ ¬(x=y)) | Uncertain |
Musicians have very busy lives.
Singh Kaur is a musician and famous.
If a musician is not famous, that musician will not make a lot of money.
A musician can be a singer or a writer. | ∀x (Musician(x) → Have(x, busyLife))
Musician(singhKaur) ∧ Famous(singhKaur)
∀x (Musician(x) ∧ ¬Famous(x) → ¬MakeALotOfMoney(x))
∃x (Musician(x) ∧ (Singer(x) ∨ Writer(x))) | Singh Kaur makes a lot of money. | MakeALotOfMoney(singhKaur) | Uncertain |
Musicians have very busy lives.
Singh Kaur is a musician and famous.
If a musician is not famous, that musician will not make a lot of money.
A musician can be a singer or a writer. | ∀x (Musician(x) → Have(x, busyLife))
Musician(singhKaur) ∧ Famous(singhKaur)
∀x (Musician(x) ∧ ¬Famous(x) → ¬MakeALotOfMoney(x))
∃x (Musician(x) ∧ (Singer(x) ∨ Writer(x))) | Singh Kaur is a writer. | Writer(singhKaur) | Uncertain |
Musicians have very busy lives.
Singh Kaur is a musician and famous.
If a musician is not famous, that musician will not make a lot of money.
A musician can be a singer or a writer. | ∀x (Musician(x) → Have(x, busyLife))
Musician(singhKaur) ∧ Famous(singhKaur)
∀x (Musician(x) ∧ ¬Famous(x) → ¬MakeALotOfMoney(x))
∃x (Musician(x) ∧ (Singer(x) ∨ Writer(x))) | Singh Kaur has a very busy life. | Have(singhKaur, busyLife) | True |
Each building is tall.
Everything tall has height. | ∀x (Building(x) → Tall(x))
∀x (Tall(x) → Height(x)) | All buildings are magnificent. | ∀x (Building(x) → Magnificent(x)) | Uncertain |
All humans are capable of abstract thoughts.
Plants are not capable of abstract thoughts.
All multicellular creatures that are autotrophic or digest food internally are plants and animals.
All goats are animals.
Dirt is not an animal.
Hulu is a goat or a human.
Hulu is a multicellular creature that is autotrophic or di... | ∀x (Human(x) → CapableOf(x, abstractThought))
∀x (Plant(x) → ¬CapableOf(x, abstractThought))
∀x (MulticellularCreature(x) ∧ (Autotrophic(x) ∨ DigestFoodInternally (x)) → Plant(x) ⊕ Animal(x))
∀x (Goat(x) → Animal(x))
∀x (Dirt(x) → ¬Animal(x))
Goat(hulu) ∨ HumanBeing(hulu)
(MulticellularCreature(hulu) ∧ (Autotrophic(hul... | Hulu is capable of abstract thoughts. | CapableOf(hulu, abstractThought) | Uncertain |
All humans are capable of abstract thoughts.
Plants are not capable of abstract thoughts.
All multicellular creatures that are autotrophic or digest food internally are plants and animals.
All goats are animals.
Dirt is not an animal.
Hulu is a goat or a human.
Hulu is a multicellular creature that is autotrophic or di... | ∀x (Human(x) → CapableOf(x, abstractThought))
∀x (Plant(x) → ¬CapableOf(x, abstractThought))
∀x (MulticellularCreature(x) ∧ (Autotrophic(x) ∨ DigestFoodInternally (x)) → Plant(x) ⊕ Animal(x))
∀x (Goat(x) → Animal(x))
∀x (Dirt(x) → ¬Animal(x))
Goat(hulu) ∨ HumanBeing(hulu)
(MulticellularCreature(hulu) ∧ (Autotrophic(hul... | Hulu is not capable of abstract thoughts. | ¬CapableOf(hulu, abstractThought) | Uncertain |
A controlled substance is a drug.
There exist both harmful and beneficial controlled substances.
If a child is exposed to a controlled substance, they are in chemical endangerment.
Chemical Endangerment is harmful.
The Controlled Substances Act was an act passed in 1971.
Some Acts prevent harmful things. | ∀x (ControlledSubstances(x) → Drugs(x))
∃x ∃y (ControlledSubstances(x) ∧ ControlledSubstances(y) ∧ (¬(x=y)) ∧ Beneficial(x) ∧ Harmful(y))
∀x ∀y ((Child(x) ∧ ControlledSubstances(y) ∧ ExposedTo(x, y)) → InChemicalEndangerment(x))
∀x (InChemicalEndangerment(x) → Harmful(x))
PassedIn(controlledSubstancesAct, yr1971) ∧ Act... | The Controlled Substances Act prevents harmful things. | PreventsHarm(controlledSubstancesAct) | Uncertain |
A controlled substance is a drug.
There exist both harmful and beneficial controlled substances.
If a child is exposed to a controlled substance, they are in chemical endangerment.
Chemical Endangerment is harmful.
The Controlled Substances Act was an act passed in 1971.
Some Acts prevent harmful things. | ∀x (ControlledSubstances(x) → Drugs(x))
∃x ∃y (ControlledSubstances(x) ∧ ControlledSubstances(y) ∧ (¬(x=y)) ∧ Beneficial(x) ∧ Harmful(y))
∀x ∀y ((Child(x) ∧ ControlledSubstances(y) ∧ ExposedTo(x, y)) → InChemicalEndangerment(x))
∀x (InChemicalEndangerment(x) → Harmful(x))
PassedIn(controlledSubstancesAct, yr1971) ∧ Act... | Some drugs are beneficial. | ∃x (Drugs(x) ∧ Beneficial(x)) | True |
A controlled substance is a drug.
There exist both harmful and beneficial controlled substances.
If a child is exposed to a controlled substance, they are in chemical endangerment.
Chemical Endangerment is harmful.
The Controlled Substances Act was an act passed in 1971.
Some Acts prevent harmful things. | ∀x (ControlledSubstances(x) → Drugs(x))
∃x ∃y (ControlledSubstances(x) ∧ ControlledSubstances(y) ∧ (¬(x=y)) ∧ Beneficial(x) ∧ Harmful(y))
∀x ∀y ((Child(x) ∧ ControlledSubstances(y) ∧ ExposedTo(x, y)) → InChemicalEndangerment(x))
∀x (InChemicalEndangerment(x) → Harmful(x))
PassedIn(controlledSubstancesAct, yr1971) ∧ Act... | A child in chemical endangerment is in harm. | ∀x ((Child(x) ∧ InChemicalEndangerment(x) → Harmful(x))) | True |
No people who have corporate jobs are taking more than normal financial risks.
All entrepreneurs are taking more than normal financial risks.
All risk-averse working people are people who have corporate jobs.
All working people who hate working for others want to be entrepreneurs.
If Mark Zuckerberg is neither an entre... | ∀x (Have(x, corporateJob) → ¬Take(x, financialRisk))
∀x (Entrepreneur(x) → Take(x, financialRisk))
∀x (RiskAverse(x) → Have(x, corporateJob))
∀x ∀y (∃y ∃z (¬(y=x) ∧ ¬(z=x) ∧ ¬(y=z) ∧ HateWorkingFor(x, y) ∧ HateWorkingFor(x, z)) → Entrepreneur(x))
¬Entrepreneur(markZuckerberg) ∧ ¬(∃y ∃z (¬(y=markZuckerberg) ∧ ¬(z=markZu... | Mark Zuckerberg is an entrepreneur. | Entrepreneur(markZuckerberg) | Uncertain |
No people who have corporate jobs are taking more than normal financial risks.
All entrepreneurs are taking more than normal financial risks.
All risk-averse working people are people who have corporate jobs.
All working people who hate working for others want to be entrepreneurs.
If Mark Zuckerberg is neither an entre... | ∀x (Have(x, corporateJob) → ¬Take(x, financialRisk))
∀x (Entrepreneur(x) → Take(x, financialRisk))
∀x (RiskAverse(x) → Have(x, corporateJob))
∀x ∀y (∃y ∃z (¬(y=x) ∧ ¬(z=x) ∧ ¬(y=z) ∧ HateWorkingFor(x, y) ∧ HateWorkingFor(x, z)) → Entrepreneur(x))
¬Entrepreneur(markZuckerberg) ∧ ¬(∃y ∃z (¬(y=markZuckerberg) ∧ ¬(z=markZu... | Mark Zuckerberg is a risk-averse person. | RiskAverse(markZuckerberg) | False |
No people who have corporate jobs are taking more than normal financial risks.
All entrepreneurs are taking more than normal financial risks.
All risk-averse working people are people who have corporate jobs.
All working people who hate working for others want to be entrepreneurs.
If Mark Zuckerberg is neither an entre... | ∀x (Have(x, corporateJob) → ¬Take(x, financialRisk))
∀x (Entrepreneur(x) → Take(x, financialRisk))
∀x (RiskAverse(x) → Have(x, corporateJob))
∀x ∀y (∃y ∃z (¬(y=x) ∧ ¬(z=x) ∧ ¬(y=z) ∧ HateWorkingFor(x, y) ∧ HateWorkingFor(x, z)) → Entrepreneur(x))
¬Entrepreneur(markZuckerberg) ∧ ¬(∃y ∃z (¬(y=markZuckerberg) ∧ ¬(z=markZu... | Mark Zuckerberg is not a risk-averse person. | ¬RiskAverse(markZuckerberg) | True |
Wildfeed exists as an unannounced program.
Wildfeed can be sporting events, news, or syndicated shows.
Pre-recorded content is a copyright violation.
Programs are pre-recorded. | ∃x (Wildfeed(x) ∧ Unannounced(x) ∧ Program(x))
∀x (Wildfeed(x) → SportingEvent(x) ∨ News(x) ∨ SyndicatedShow(x))
∀x (Prerecorded(x) → CopyrightViolation(x))
∀x (Program(x) → Prerecorded(x)) | Some wildfeed is violating copyright laws. | ∃x (Wildfeed(x) ∧ CopyrightViolation(x)) | True |
Wildfeed exists as an unannounced program.
Wildfeed can be sporting events, news, or syndicated shows.
Pre-recorded content is a copyright violation.
Programs are pre-recorded. | ∃x (Wildfeed(x) ∧ Unannounced(x) ∧ Program(x))
∀x (Wildfeed(x) → SportingEvent(x) ∨ News(x) ∨ SyndicatedShow(x))
∀x (Prerecorded(x) → CopyrightViolation(x))
∀x (Program(x) → Prerecorded(x)) | Wildfeed can be prerecorded. | ∃x (Wildfeed(x) ∧ Prerecorded(x)) | True |
Wildfeed exists as an unannounced program.
Wildfeed can be sporting events, news, or syndicated shows.
Pre-recorded content is a copyright violation.
Programs are pre-recorded. | ∃x (Wildfeed(x) ∧ Unannounced(x) ∧ Program(x))
∀x (Wildfeed(x) → SportingEvent(x) ∨ News(x) ∨ SyndicatedShow(x))
∀x (Prerecorded(x) → CopyrightViolation(x))
∀x (Program(x) → Prerecorded(x)) | Syndicated shows are copyright violations. | ∃x (SyndicatedShow(x) ∧ CopyrightViolation(x)) | Uncertain |
New York City is Located in the United States of America.
The United States of America is part of North America.
North America is in the western hemisphere of the earth.
New York City is a highly developed city.
If place A is located in place B and place B is located in place C, then place A is located in place C. | LocatedIn(newYorkCity, unitedStatesOfAmerica)
LocatedIn(usa, northAmerica)
LocatedIn(northAmerica, westernHemisphere)
HighlyDeveloped(newYorkCity)
∀x ∀y ∀z ((LocatedIn(x, y) ∧ LocatedIn(y, z)) → LocatedIn(x, z)) | New York City is located in New York State. | LocatedIn(newYorkCity, newYork) | Uncertain |
Catullus 4 is a poem written by the ancient Roman writer Catullus.
Catullus 4 is a story about the retirement of a well-traveled ship.
There is a strong analogy of human aging in the poem Catullus 4.
Catullus 4 is written in an unusual iambic trimeter to convey a sense of speed over the waves. | Poem(catullus4) ∧ WrittenBy(catullus4, catullus) ∧ AncientRomanWriter(catullus)
Story(catullus4) ∧ About(catullus4, retirementOfAWellTraveledShip)
Poem(catullus4) ∧ StrongAgingAnalogy(catullus4)
Poem(catullus4) ∧ WrittenIn(catullus4, iambicTrimeter) ∧ Convey(catullus4, aSenseOfSpeedOverTheWaves) | There is a poem written by an ancient Roman writer with a strong analogy of human aging. | ∃x ∃y (Poem(x) ∧ WrittenBy(x, y) ∧ AncientRomanWriter(y) ∧ StrongAgingAnalogy(x)) | True |
Catullus 4 is a poem written by the ancient Roman writer Catullus.
Catullus 4 is a story about the retirement of a well-traveled ship.
There is a strong analogy of human aging in the poem Catullus 4.
Catullus 4 is written in an unusual iambic trimeter to convey a sense of speed over the waves. | Poem(catullus4) ∧ WrittenBy(catullus4, catullus) ∧ AncientRomanWriter(catullus)
Story(catullus4) ∧ About(catullus4, retirementOfAWellTraveledShip)
Poem(catullus4) ∧ StrongAgingAnalogy(catullus4)
Poem(catullus4) ∧ WrittenIn(catullus4, iambicTrimeter) ∧ Convey(catullus4, aSenseOfSpeedOverTheWaves) | Callus 4 is written in an unusual iambic trimeter to convey a strong analogy of human aging. | Poem(catullus4) ∧ WrittenIn(catullus4, iambicTrimeter) ∧ StrongAgingAnalogy(catullus4) | True |
Westworld is an American science fiction-thriller TV series.
In 2016, a television series named Westworld debuted on HBO.
The TV series Westworld is adapted from the original film in 1973, which was written and directed by Michael Crichton.
The 1973 film Westworld is about robots that malfunction and begin killing huma... | American(westworld) ∧ ScienceFictionThriller(westworld)
Debut(westworld, year2016) ∧ TvSeries(westworld)
Adapted(westworld, westworldTheFilm) ∧ Produce(westworldTheFilm, year1973) ∧ Wrote(michael, westworldTheFilm) ∧ Directed(michael, westworldTheFilm)
Film(westworldTheFilm) ∧ About(westworldTheFilm, malfunctioningRobo... | Michael Crichton has directed a film about malfunctioning robots. | ∃x (Film(x) ∧ Directed(michael, x) ∧ About(x, malfunctioningRobots)) | True |
Westworld is an American science fiction-thriller TV series.
In 2016, a television series named Westworld debuted on HBO.
The TV series Westworld is adapted from the original film in 1973, which was written and directed by Michael Crichton.
The 1973 film Westworld is about robots that malfunction and begin killing huma... | American(westworld) ∧ ScienceFictionThriller(westworld)
Debut(westworld, year2016) ∧ TvSeries(westworld)
Adapted(westworld, westworldTheFilm) ∧ Produce(westworldTheFilm, year1973) ∧ Wrote(michael, westworldTheFilm) ∧ Directed(michael, westworldTheFilm)
Film(westworldTheFilm) ∧ About(westworldTheFilm, malfunctioningRobo... | An American TV series debuted in 2016. | ∃x (TVSeries(x) ∧ American(x) ∧ Debut(x, year2016)) | True |
Xiufeng, Xiangshan, Diecai, Qixing are districts in the city of Guilin.
Yangshuo is not a district in Guilin. | DistrictIn(xiufeng, guilin) ∧ DistrictIn(xiangshan, guilin) ∧ DistrictIn(diecai, guilin) ∧ DistrictIn(qixing, guilin) ∧ City(guilin)
¬DistrictIn(yangshuo, guilin) | Xiangshan and Diecai are districts in the same city. | ∃x (DistrictIn(xiangshan, x) ∧ DistrictIn(diecai, x) ∧ City(x)) | True |
Xiufeng, Xiangshan, Diecai, Qixing are districts in the city of Guilin.
Yangshuo is not a district in Guilin. | DistrictIn(xiufeng, guilin) ∧ DistrictIn(xiangshan, guilin) ∧ DistrictIn(diecai, guilin) ∧ DistrictIn(qixing, guilin) ∧ City(guilin)
¬DistrictIn(yangshuo, guilin) | Xiufeng is a district in Guilin. | DistrictIn(xiufeng, guilin) | True |
Xiufeng, Xiangshan, Diecai, Qixing are districts in the city of Guilin.
Yangshuo is not a district in Guilin. | DistrictIn(xiufeng, guilin) ∧ DistrictIn(xiangshan, guilin) ∧ DistrictIn(diecai, guilin) ∧ DistrictIn(qixing, guilin) ∧ City(guilin)
¬DistrictIn(yangshuo, guilin) | Kowloon District is in Hong Kong. | DistrictIn(kowloon, hongKong) | Uncertain |
All of Michael's neighbors who grow their own fresh vegetables in their home gardens also have ample space.
All of Michael's neighbors who are young working professionals and live in large cities, do not have ample space.
All of Michael's neighbors who order takeout from delivery services often grow their own fresh veg... | ∀x (MichaelsNeightbor(x) ∧ GrowIn(x, vegetable, garden) → Have(x, ampleSpace))
∀x (MichaelsNeightbor(x) ∧ YoungWorkingProfession(x) ∧ LiveIn(x, largeCity) → ¬Have(x, ampleSpace))
∀x (MichaelsNeightbor(x) ∧ OrderOften(x, takeout) → GrowIn(x, vegetable, garden))
∀x (MichaelsNeightbor(x) ∧ EnjoyGoingOutOftenToWith(x, rest... | Peter enjoys going out often to restaurants with friends. | EnjoyGoingOutOftenToWith(peter, restaurant, friend) | Uncertain |
All of Michael's neighbors who grow their own fresh vegetables in their home gardens also have ample space.
All of Michael's neighbors who are young working professionals and live in large cities, do not have ample space.
All of Michael's neighbors who order takeout from delivery services often grow their own fresh veg... | ∀x (MichaelsNeightbor(x) ∧ GrowIn(x, vegetable, garden) → Have(x, ampleSpace))
∀x (MichaelsNeightbor(x) ∧ YoungWorkingProfession(x) ∧ LiveIn(x, largeCity) → ¬Have(x, ampleSpace))
∀x (MichaelsNeightbor(x) ∧ OrderOften(x, takeout) → GrowIn(x, vegetable, garden))
∀x (MichaelsNeightbor(x) ∧ EnjoyGoingOutOftenToWith(x, rest... | Peter is a young working professional who lives in large cities. | YoungWorkingProfession(peter) ∧ LiveIn(peter, largeCity) | False |
All of Michael's neighbors who grow their own fresh vegetables in their home gardens also have ample space.
All of Michael's neighbors who are young working professionals and live in large cities, do not have ample space.
All of Michael's neighbors who order takeout from delivery services often grow their own fresh veg... | ∀x (MichaelsNeightbor(x) ∧ GrowIn(x, vegetable, garden) → Have(x, ampleSpace))
∀x (MichaelsNeightbor(x) ∧ YoungWorkingProfession(x) ∧ LiveIn(x, largeCity) → ¬Have(x, ampleSpace))
∀x (MichaelsNeightbor(x) ∧ OrderOften(x, takeout) → GrowIn(x, vegetable, garden))
∀x (MichaelsNeightbor(x) ∧ EnjoyGoingOutOftenToWith(x, rest... | Peter grows his own fresh vegetables in their home garden or is a young working professional who lives in large cities. | GrowIn(peter, vegetable, garden) ∨ (YoungWorkingProfession(peter) ∧ LiveIn(peter, largeCity)) | True |
All devices belonging to the company are connected to Google Home.
All devices belonging to employees are connected to the company's wifi.
All devices connected to Google Home are controlled by the managers.
All devices that connect to the company's wifi are easy to operate.
ModelXX belongs to employees. | ∀x (OwnedBy(x, company) → ConnectedTo(x, googleHome))
∀x (OwnedBy(x, employee) → ConnectedTo(x, companyWiFi))
∀x (ConnectedTo(x, googleHome) → ControlledBy(x, managers))
∀x (ConnectedTo(x, companyWiFi) → EasyToOperate(x))
OwnedBy(modelXX, employee) | ModelXX is easy to operate. | EasyToOperate(modelXX) | True |
All devices belonging to the company are connected to Google Home.
All devices belonging to employees are connected to the company's wifi.
All devices connected to Google Home are controlled by the managers.
All devices that connect to the company's wifi are easy to operate.
ModelXX belongs to employees. | ∀x (OwnedBy(x, company) → ConnectedTo(x, googleHome))
∀x (OwnedBy(x, employee) → ConnectedTo(x, companyWiFi))
∀x (ConnectedTo(x, googleHome) → ControlledBy(x, managers))
∀x (ConnectedTo(x, companyWiFi) → EasyToOperate(x))
OwnedBy(modelXX, employee) | ModelXX is controlled by managers. | ControlledBy(modelXX, managers) | Uncertain |
All devices belonging to the company are connected to Google Home.
All devices belonging to employees are connected to the company's wifi.
All devices connected to Google Home are controlled by the managers.
All devices that connect to the company's wifi are easy to operate.
ModelXX belongs to employees. | ∀x (OwnedBy(x, company) → ConnectedTo(x, googleHome))
∀x (OwnedBy(x, employee) → ConnectedTo(x, companyWiFi))
∀x (ConnectedTo(x, googleHome) → ControlledBy(x, managers))
∀x (ConnectedTo(x, companyWiFi) → EasyToOperate(x))
OwnedBy(modelXX, employee) | ModelXX is connected to Google Home. | ConnectedTo(modelXX, googleHome) | Uncertain |
No touring musicians who perform at the New Haven Symphony Orchestra are permanent members of the orchestra.
Musicians who perform at the New Haven Symphony Orchestra are permanent members of an orchestra, or they have temporary roles at the orchestra.
All touring musicians who perform at the New Haven Symphony Orchest... | ∀x ((PerformAt(x, newHavenSymphonyOrchestra) ∧ TouringMusician(x)) → ¬PermanentMemberOf(x, theOrchestra))
∀x (PerformAt(x, newHavenSymphonyOrchestra) → (PermanentMemberOf(x, theOrchestra) ∨ HaveTemporaryRoleAt(x, theOrchestra)))
∀x ((PerformAt(x, newHavenSymphonyOrchestra) ∧ TouringMusician(x)) → HaveTemporaryRoleAt(x,... | Ryan is an interesting soloist. | InterestingSoloist(ryan) | Uncertain |
If someone in Potterville yells, then they are not cool.
If someone in Potterville is angry, then they yell.
If someone in Potterville flies, then they are cool.
Every person in Potterville that knows magic flies.
All wizards in Potterville know magic.
Harry, who lives in Potterville either yells or flies.
Potter, who... | ∀x (In(x, potterville) ∧ Yell(x) → ¬Cool(x))
∀x (In(x, potterville) ∧ Angry(x) → Yell(x))
∀x (In(x, potterville) ∧ Fly(x) → Cool(x))
∀x (In(x, potterville) ∧ Know(x, magic) → Fly(x))
∀x (In(x, potterville) ∧ Wizard(x) → Know(x, magic))
In(harry, potterville) ∧ (Yell(harry) ⊕ Fly(harry))
Wizard(potter) ∧ Fly(potter) | Harry is cool. | Cool(harry) | Uncertain |
If someone in Potterville yells, then they are not cool.
If someone in Potterville is angry, then they yell.
If someone in Potterville flies, then they are cool.
Every person in Potterville that knows magic flies.
All wizards in Potterville know magic.
Harry, who lives in Potterville either yells or flies.
Potter, who... | ∀x (In(x, potterville) ∧ Yell(x) → ¬Cool(x))
∀x (In(x, potterville) ∧ Angry(x) → Yell(x))
∀x (In(x, potterville) ∧ Fly(x) → Cool(x))
∀x (In(x, potterville) ∧ Know(x, magic) → Fly(x))
∀x (In(x, potterville) ∧ Wizard(x) → Know(x, magic))
In(harry, potterville) ∧ (Yell(harry) ⊕ Fly(harry))
Wizard(potter) ∧ Fly(potter) | Harry is not cool. | ¬Cool(harry) | Uncertain |
All of this brand's products are either produced in China or in the US.
All of this brand's products produced in China are labeled.
All of this brand's products produced in the US are sold in the US.
The products of this brand that are labeled are cheaper.
All of this brand's products sold in the US are sold at Walm... | ∀x (ThisBrand(x) ∧ Product(x) → (ProducedIn(x, china) ⊕ ProducedIn(x, uS)))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, china)) → Labeled(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, us)) → SoldIn(x, us))
∀x ((ThisBrand(x) ∧ Product(x) ∧ Labeled(x)) → Cheaper(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ SoldIn(x, us))... | G-910 is displayed on the homepage. | DisplayedIn(g910, homepage) | Uncertain |
All of this brand's products are either produced in China or in the US.
All of this brand's products produced in China are labeled.
All of this brand's products produced in the US are sold in the US.
The products of this brand that are labeled are cheaper.
All of this brand's products sold in the US are sold at Walm... | ∀x (ThisBrand(x) ∧ Product(x) → (ProducedIn(x, china) ⊕ ProducedIn(x, uS)))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, china)) → Labeled(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, us)) → SoldIn(x, us))
∀x ((ThisBrand(x) ∧ Product(x) ∧ Labeled(x)) → Cheaper(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ SoldIn(x, us))... | G-910 is not displayed on the homepage. | ¬DisplayedIn(g910, homepage) | Uncertain |
All of this brand's products are either produced in China or in the US.
All of this brand's products produced in China are labeled.
All of this brand's products produced in the US are sold in the US.
The products of this brand that are labeled are cheaper.
All of this brand's products sold in the US are sold at Walm... | ∀x (ThisBrand(x) ∧ Product(x) → (ProducedIn(x, china) ⊕ ProducedIn(x, uS)))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, china)) → Labeled(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, us)) → SoldIn(x, us))
∀x ((ThisBrand(x) ∧ Product(x) ∧ Labeled(x)) → Cheaper(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ SoldIn(x, us))... | G-910 is a product returned by customers. | ThisBrand(g910) ∧ ReturnedBy(g910, customer) | False |
All of this brand's products are either produced in China or in the US.
All of this brand's products produced in China are labeled.
All of this brand's products produced in the US are sold in the US.
The products of this brand that are labeled are cheaper.
All of this brand's products sold in the US are sold at Walm... | ∀x (ThisBrand(x) ∧ Product(x) → (ProducedIn(x, china) ⊕ ProducedIn(x, uS)))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, china)) → Labeled(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, us)) → SoldIn(x, us))
∀x ((ThisBrand(x) ∧ Product(x) ∧ Labeled(x)) → Cheaper(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ SoldIn(x, us))... | G-910 is a product returned by customers or sold in Walmart. | ThisBrand(g910) ∧ (ReturnedBy(g910, customer) ∨ SoldIn(g910, walmart)) | True |
All of this brand's products are either produced in China or in the US.
All of this brand's products produced in China are labeled.
All of this brand's products produced in the US are sold in the US.
The products of this brand that are labeled are cheaper.
All of this brand's products sold in the US are sold at Walm... | ∀x (ThisBrand(x) ∧ Product(x) → (ProducedIn(x, china) ⊕ ProducedIn(x, uS)))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, china)) → Labeled(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ ProducedIn(x, us)) → SoldIn(x, us))
∀x ((ThisBrand(x) ∧ Product(x) ∧ Labeled(x)) → Cheaper(x))
∀x ((ThisBrand(x) ∧ Product(x) ∧ SoldIn(x, us))... | G-910 is either returned by customers or sold in Walmart. | ReturnedBy(g910, customer) ⊕ SoldIn(g910, walmart) | True |
Indonesia is a country.
In Indonesia, the prosecutor only personally investigates cases of some special crimes.
Corruption is a type of crime.
Once the police complete crime investigations, the evidence is handed to the prosecutor.
Evidence can be either satisfactory or unsatisfactory.
If the evidence is handed to the... | Country(indonesia)
∀x ∃y (In(indonesia) ∧ Prosecutor(x) ∧ SpecialCrime(y) → InvestigatePersonally(x, y))
Crime(corruption)
∀x ∀y ∀z (Crime(y) ∧ PoliceCompleteInvestigation(y) ∧ Prosecutor(x) → Evidence(z) ∧ HandedTo(z, x))
∀x (Evidence(x) ∧ (Satisfactory(x) ⊕ Unsatisfactory(x)))
∀x ∀y (Evidence(y) ∧ Prosecutor(x) ∧ Han... | When the police complete investigations, the prosecutor will prosecute the offender at an appropriate court. | ∀x ∀y (Crime(y) ∧ PoliceCompleteInvestigation(y) ∧ Prosecutor(x) → ProsecuteInAppropriateCourt(x, theOffender)) | Uncertain |
Indonesia is a country.
In Indonesia, the prosecutor only personally investigates cases of some special crimes.
Corruption is a type of crime.
Once the police complete crime investigations, the evidence is handed to the prosecutor.
Evidence can be either satisfactory or unsatisfactory.
If the evidence is handed to the... | Country(indonesia)
∀x ∃y (In(indonesia) ∧ Prosecutor(x) ∧ SpecialCrime(y) → InvestigatePersonally(x, y))
Crime(corruption)
∀x ∀y ∀z (Crime(y) ∧ PoliceCompleteInvestigation(y) ∧ Prosecutor(x) → Evidence(z) ∧ HandedTo(z, x))
∀x (Evidence(x) ∧ (Satisfactory(x) ⊕ Unsatisfactory(x)))
∀x ∀y (Evidence(y) ∧ Prosecutor(x) ∧ Han... | In Indonesia, the prosecutor personally investigates cases of corruption. | ∀x (Country(indonesia) ∧ Prosecutor(x) ∧ Crime(corruption) → InvestigatePersonally(x, corruption)) | Uncertain |
Indonesia is a country.
In Indonesia, the prosecutor only personally investigates cases of some special crimes.
Corruption is a type of crime.
Once the police complete crime investigations, the evidence is handed to the prosecutor.
Evidence can be either satisfactory or unsatisfactory.
If the evidence is handed to the... | Country(indonesia)
∀x ∃y (In(indonesia) ∧ Prosecutor(x) ∧ SpecialCrime(y) → InvestigatePersonally(x, y))
Crime(corruption)
∀x ∀y ∀z (Crime(y) ∧ PoliceCompleteInvestigation(y) ∧ Prosecutor(x) → Evidence(z) ∧ HandedTo(z, x))
∀x (Evidence(x) ∧ (Satisfactory(x) ⊕ Unsatisfactory(x)))
∀x ∀y (Evidence(y) ∧ Prosecutor(x) ∧ Han... | When the police complete investigations, the prosecutor investigates personally. | ∀x ∀y (Crime(y) ∧ PoliceCompleteInvestigation(y) ∧ Prosecutor(x) → InvestigatePersonally(x, y)) | Uncertain |
No battery-powered watch is automatic.
All digital watches are battery-powered.
Some mechanical watches are automatic.
All smart watches are digital.
Moonwatch is either a digital watch and an automatic, or it is neither. | ∀x (BatteryPoweredWatch(x) → ¬AutomaticWatch(x))
∀x (DigitalWatch(x) → BatteryPoweredWatch(x))
∃x (MechanicalWatch(x) ∧ AutomaticWatch(x))
∀x (SmartWatch(x) → DigitalWatch(x))
¬(DigitalWatch(moonwatch) ⊕ AutomaticWatch(moonwatch)) | Moonwatch is a mechanical watch. | MechanicalWatch(moonWatch) | Uncertain |
No battery-powered watch is automatic.
All digital watches are battery-powered.
Some mechanical watches are automatic.
All smart watches are digital.
Moonwatch is either a digital watch and an automatic, or it is neither. | ∀x (BatteryPoweredWatch(x) → ¬AutomaticWatch(x))
∀x (DigitalWatch(x) → BatteryPoweredWatch(x))
∃x (MechanicalWatch(x) ∧ AutomaticWatch(x))
∀x (SmartWatch(x) → DigitalWatch(x))
¬(DigitalWatch(moonwatch) ⊕ AutomaticWatch(moonwatch)) | Moonwatch is a smartwatch and a mechanical watch. | SmartWatch(moonwatch) ∧ MechanicalWatch(moonwatch) | False |
No battery-powered watch is automatic.
All digital watches are battery-powered.
Some mechanical watches are automatic.
All smart watches are digital.
Moonwatch is either a digital watch and an automatic, or it is neither. | ∀x (BatteryPoweredWatch(x) → ¬AutomaticWatch(x))
∀x (DigitalWatch(x) → BatteryPoweredWatch(x))
∃x (MechanicalWatch(x) ∧ AutomaticWatch(x))
∀x (SmartWatch(x) → DigitalWatch(x))
¬(DigitalWatch(moonwatch) ⊕ AutomaticWatch(moonwatch)) | If Moonwatch is a smartwatch and a mechanical watch, then Moonwatch is not a mechanical watch. | SmartWatch(moonwatch) ∧ MechanicalWatch(moonwatch) → ¬MechanicalWatch(moonwatch) | True |
No battery-powered watch is automatic.
All digital watches are battery-powered.
Some mechanical watches are automatic.
All smart watches are digital.
Moonwatch is either a digital watch and an automatic, or it is neither. | ∀x (BatteryPoweredWatch(x) → ¬AutomaticWatch(x))
∀x (DigitalWatch(x) → BatteryPoweredWatch(x))
∃x (MechanicalWatch(x) ∧ AutomaticWatch(x))
∀x (SmartWatch(x) → DigitalWatch(x))
¬(DigitalWatch(moonwatch) ⊕ AutomaticWatch(moonwatch)) | If Moonwatch is a mechanical or battery-powered watch, then Moonwatch is not a smartwatch. | MechanicalWatch(moonwatch) ∨ BatteryPoweredWatch(moonwatch) → ¬SmartWatch(moonwatch) | True |
Video Gag is a French television series that airs weekly.
Video Gag airs on the French broadcast channel TF1.
If viewers send funny videos to the French broadcast channel TF1, then Video Gag airs them weekly.
All videos aired on Video Gag are in French. | FrenchTelevision(videoGag) ∧ AirWeekly(videoGag)
AirOn(videoGag, frenchBroadcastChannelTF1)
∀x (Funny(x) ∧ Video(x) ∧ SendIn(viewers, x, frenchBroadcastChannelTF1) → AirWeekly(x) ) ∧ AirOn(videoGag, x)
∀x (Video(x) ∧ AirOn(videoGag, x) → In(x, french)) | Viewers send funny videos to the French broadcast channel TF1 that are in French. | ∃x (SendIn(viewers, x, frenchBroadcastChannelTF1) ∧ French(x)) | Uncertain |
Video Gag is a French television series that airs weekly.
Video Gag airs on the French broadcast channel TF1.
If viewers send funny videos to the French broadcast channel TF1, then Video Gag airs them weekly.
All videos aired on Video Gag are in French. | FrenchTelevision(videoGag) ∧ AirWeekly(videoGag)
AirOn(videoGag, frenchBroadcastChannelTF1)
∀x (Funny(x) ∧ Video(x) ∧ SendIn(viewers, x, frenchBroadcastChannelTF1) → AirWeekly(x) ) ∧ AirOn(videoGag, x)
∀x (Video(x) ∧ AirOn(videoGag, x) → In(x, french)) | Viewers send funny videos to the French broadcast channel that are in English. | ∃x (SendIn(viewers, x, frenchBroadcastChannelTF1) ∧ English(x)) | Uncertain |
All phones are things.
All cell phones are phones.
All iPhones are cell phones.
All employees are wage earners.
All wage earners are human.
Jack is either an employee or a wage earner.
Jack is either a human or a phone. | ∀x (Phone(x) → Thing(x))
∀x (Cellphone(x) → Phone(x))
∀x (Iphone(x) → Cellphone(x))
∀x (Employee(x) → WageEarner(x))
∀x (WageEarner(x) → Human(x))
Employee(jack) ⊕ WageEarner(jack)
Human(jack) ⊕ Phone(jack) | Jack is a thing. | Thing(jack) | Uncertain |
All phones are things.
All cell phones are phones.
All iPhones are cell phones.
All employees are wage earners.
All wage earners are human.
Jack is either an employee or a wage earner.
Jack is either a human or a phone. | ∀x (Phone(x) → Thing(x))
∀x (Cellphone(x) → Phone(x))
∀x (Iphone(x) → Cellphone(x))
∀x (Employee(x) → WageEarner(x))
∀x (WageEarner(x) → Human(x))
Employee(jack) ⊕ WageEarner(jack)
Human(jack) ⊕ Phone(jack) | Jack is not a thing. | ¬Thing(jack) | Uncertain |
All phones are things.
All cell phones are phones.
All iPhones are cell phones.
All employees are wage earners.
All wage earners are human.
Jack is either an employee or a wage earner.
Jack is either a human or a phone. | ∀x (Phone(x) → Thing(x))
∀x (Cellphone(x) → Phone(x))
∀x (Iphone(x) → Cellphone(x))
∀x (Employee(x) → WageEarner(x))
∀x (WageEarner(x) → Human(x))
Employee(jack) ⊕ WageEarner(jack)
Human(jack) ⊕ Phone(jack) | Jack is a thing and an iPhone. | Thing(jack) ∧ Phone(jack) | False |
All phones are things.
All cell phones are phones.
All iPhones are cell phones.
All employees are wage earners.
All wage earners are human.
Jack is either an employee or a wage earner.
Jack is either a human or a phone. | ∀x (Phone(x) → Thing(x))
∀x (Cellphone(x) → Phone(x))
∀x (Iphone(x) → Cellphone(x))
∀x (Employee(x) → WageEarner(x))
∀x (WageEarner(x) → Human(x))
Employee(jack) ⊕ WageEarner(jack)
Human(jack) ⊕ Phone(jack) | Jack is not both a thing and an iPhone. | ¬(Thing(jack) ∧ Phone(jack)) | True |
The Metropolitan Museum of Art is a museum in NYC.
Whitney Museum of American Art is a museum in NYC.
The Museum of Modern Art (MoMA) is a museum in NYC.
The Metropolitan Museum of Art includes Byzantine and Islamic Art.
Whitney Museum of American Art includes American art. | Museum(metropolitanMuseumOfArt) ∧ In(metropolitanMuseumOfArt, nYC)
Museum(whitneyMuseumOfAmericanArt) ∧ In(metropolitanMuseumOfArt, nYC)
Museum(museumOfModernArt) ∧ In(museumOfModernArt, nYC)
Include(metropolitanMuseumOfArt, byzantineArt) ∧ Include(metropolitanMuseumOfArt, islamicArt)
Include(whitneyMuseumOfAmericanArt... | A museum in NYC includes Byzantine and Islamic Art. | ∃x (Museum(x) ∧ In(x, nYC) ∧ Include(x, byzantineArt) ∧ Include(x, islamicArt)) | True |
The Metropolitan Museum of Art is a museum in NYC.
Whitney Museum of American Art is a museum in NYC.
The Museum of Modern Art (MoMA) is a museum in NYC.
The Metropolitan Museum of Art includes Byzantine and Islamic Art.
Whitney Museum of American Art includes American art. | Museum(metropolitanMuseumOfArt) ∧ In(metropolitanMuseumOfArt, nYC)
Museum(whitneyMuseumOfAmericanArt) ∧ In(metropolitanMuseumOfArt, nYC)
Museum(museumOfModernArt) ∧ In(museumOfModernArt, nYC)
Include(metropolitanMuseumOfArt, byzantineArt) ∧ Include(metropolitanMuseumOfArt, islamicArt)
Include(whitneyMuseumOfAmericanArt... | A museum in NYC includes Greek art. | ∃x (Museum(x) ∧ In(x, nYC) ∧ Include(x, greekArt)) | Uncertain |
Gasteren is a village located in the province of Drenthe.
Drenthe is a Dutch province.
No cities are villages.
The population of a village in Drenthe was 155 people. | Village(gasteren) ∧ Province(drenthe) ∧ In(gasteren, drenthe)
Province(drenthe) ∧ In(drenthe, netherlands)
∀x (City(x) → ¬Village(x))
∃x (Population(x, num155) ∧ Village(x) ∧ In(x, drenthe)) | Gasteren is a Dutch village. | Village(gasteren) ∧ In(gasteren, netherlands) | Uncertain |
Gasteren is a village located in the province of Drenthe.
Drenthe is a Dutch province.
No cities are villages.
The population of a village in Drenthe was 155 people. | Village(gasteren) ∧ Province(drenthe) ∧ In(gasteren, drenthe)
Province(drenthe) ∧ In(drenthe, netherlands)
∀x (City(x) → ¬Village(x))
∃x (Population(x, num155) ∧ Village(x) ∧ In(x, drenthe)) | Gasteren is a city. | City(gasteren) | False |
Gasteren is a village located in the province of Drenthe.
Drenthe is a Dutch province.
No cities are villages.
The population of a village in Drenthe was 155 people. | Village(gasteren) ∧ Province(drenthe) ∧ In(gasteren, drenthe)
Province(drenthe) ∧ In(drenthe, netherlands)
∀x (City(x) → ¬Village(x))
∃x (Population(x, num155) ∧ Village(x) ∧ In(x, drenthe)) | Gasteren has a population of 155. | Population(gasteren, num155) | Uncertain |
The only types of mammals that lay eggs are either platypuses or echidnas.
Platypuses are not hyrax.
Echidnas are not hyrax.
No mammals are invertebrates.
All animals are either vertebrates or invertebrates.
Mammals are animals.
Hyraxes are mammals.
Grebes lay eggs.
Grebes are not platypuses and also not echidnas. | ∀x ((Mammal(x) ∧ LayEgg(x)) → (Platypus(x) ⊕ Echidnas(x)))
∀x (Platypuses(x) → ¬Hyrax(x))
∀x (Echidnas(x) → ¬Hyrax(x))
∀x (Mammal(x) → ¬Invertebrate(x))
∀x (Animal(x) → (Vertebrate(x) ∨ Invertebrate(x)))
∀x (Mammal(x) → Animal(x))
∀x (Hyrax(x) → Mammal(x))
∀x (Grebes(x) → LayEgg(x))
∀x (Grebes(x) → (¬Platypuses(x) ∧ ¬E... | Platypuses are vertebrates. | ∀x (Platypuses(x) → Vertebrate(x)) | Uncertain |
Bobby Flynn is a singer-songwriter.
Bobby Flynn finished 7th while competing on Australian Idol.
Australian Idol competitors are Australian citizens.
The Omega Three band made a nationwide tour in 2007.
Bobby Flynn is a member of The Omega Three band.
Bobby Flynn was born in Queensland. | Singer(bobbyFlynn) ∧ SongWriter(bobbyFlynn)
FinishesIn(bobbyFlynn, number7) ∧ CompetesOnAustralianIdol(bobbyFlynn)
∀x (CompetesOnAustralianIdol(x) → AustralianCitizen(x))
NationWideTourIn(theOmegaThreeBand, year2007)
Member(bobbyFlynn, theOmegaThreeBand)
BornIn(bobbyFlynn, queensland) | Bobby Flynn is an Australian citizen. | AustralianCitizen(bobbyFlynn) | True |
Bobby Flynn is a singer-songwriter.
Bobby Flynn finished 7th while competing on Australian Idol.
Australian Idol competitors are Australian citizens.
The Omega Three band made a nationwide tour in 2007.
Bobby Flynn is a member of The Omega Three band.
Bobby Flynn was born in Queensland. | Singer(bobbyFlynn) ∧ SongWriter(bobbyFlynn)
FinishesIn(bobbyFlynn, number7) ∧ CompetesOnAustralianIdol(bobbyFlynn)
∀x (CompetesOnAustralianIdol(x) → AustralianCitizen(x))
NationWideTourIn(theOmegaThreeBand, year2007)
Member(bobbyFlynn, theOmegaThreeBand)
BornIn(bobbyFlynn, queensland) | Bobby Flynn flew to America in 2007. | FlewToIn(bobbyFlynn, america, year2007) | Uncertain |
Bobby Flynn is a singer-songwriter.
Bobby Flynn finished 7th while competing on Australian Idol.
Australian Idol competitors are Australian citizens.
The Omega Three band made a nationwide tour in 2007.
Bobby Flynn is a member of The Omega Three band.
Bobby Flynn was born in Queensland. | Singer(bobbyFlynn) ∧ SongWriter(bobbyFlynn)
FinishesIn(bobbyFlynn, number7) ∧ CompetesOnAustralianIdol(bobbyFlynn)
∀x (CompetesOnAustralianIdol(x) → AustralianCitizen(x))
NationWideTourIn(theOmegaThreeBand, year2007)
Member(bobbyFlynn, theOmegaThreeBand)
BornIn(bobbyFlynn, queensland) | Bobby Flynn was born in Queens. | BornIn(bobbyFlynn, queens) | Uncertain |
All proteins are organic compounds.
All enzymes are organic compounds. | ∀x (Protein(x) → OrganicCompound(x))
∀x (Enzyme(x) → OrganicCompound(x)) | All enzymes are proteins. | ∀x (Enzyme(x) → Protein(x)) | Uncertain |
Maggie Friedman is an American screenwriter and producer.
Maggie Friedman was the showrunner and executive producer of the lifetime television series Witches of East End.
Witches of East End is a fantasy-drama series.
Maggie Friedman produced and developed Eastwick.
Eastwick is a series by ABC. | American(maggieFriedman) ∧ Screenwriter(maggieFriedman) ∧ Producer(maggieFriedman)
ShowRunnerOf(maggieFriedman, witchesOfEastEnd) ∧ ExecutiveProducerOf(maggieFriedman, witchesOfEastEnd) ∧ LifetimeTelevisionSeries(maggieFriedman)
FantasyDrama(witchesOfEastEnd) ∧ Series(witchesOfEastEnd)
Produces(maggieFriedman, eastwick... | There is a series by ABC that was developed by the showrunner of Witches of East End. | ∃x ∃y (Series(x) ∧ AiredOn(x, aBC) ∧ Develops(y, x) ∧ ShowRunnerOf(y, witchesOfEastEnd)) | True |
Maggie Friedman is an American screenwriter and producer.
Maggie Friedman was the showrunner and executive producer of the lifetime television series Witches of East End.
Witches of East End is a fantasy-drama series.
Maggie Friedman produced and developed Eastwick.
Eastwick is a series by ABC. | American(maggieFriedman) ∧ Screenwriter(maggieFriedman) ∧ Producer(maggieFriedman)
ShowRunnerOf(maggieFriedman, witchesOfEastEnd) ∧ ExecutiveProducerOf(maggieFriedman, witchesOfEastEnd) ∧ LifetimeTelevisionSeries(maggieFriedman)
FantasyDrama(witchesOfEastEnd) ∧ Series(witchesOfEastEnd)
Produces(maggieFriedman, eastwick... | Maggie Friedman developed Witches of East End. | Develops(maggieFriedman, witchesOfEastEnd) | Uncertain |
Boney M. had several German #1 singles.
"Hooray! Hooray! It's a Holi-Holiday!" was a big hit all over Europe.
"Hooray! Hooray! It's a Holi-Holiday!" was not in German #1 singles.
A song that peaks below #1 on the german charts is also a song that is not the #1 single in Germany. | ∃x (Song(x) ∧ By(x, boneym,) ∧ Number1GermanSingle(x))
Song(hoorayHoorayItsAHoliHoliday) ∧ HitAllOverEurope(hoorayHoorayItsAHoliHoliday)
Song(hoorayHoorayItsAHoliHoliday) ∧ ¬Number1GermanSingle(hoorayHoorayItsAHoliHoliday)
∀x (PeakBelowOn(x, number1, germanChart) → ¬Number1GermanSingle(x)) | "Hooray! Hooray! It's a Holi-Holiday!" was the #1 hit in Germany. | Song(hoorayHoorayItsAHoliHoliday) ∧ Number1GermanSingle(hoorayHoorayItsAHoliHoliday) | False |
Boney M. had several German #1 singles.
"Hooray! Hooray! It's a Holi-Holiday!" was a big hit all over Europe.
"Hooray! Hooray! It's a Holi-Holiday!" was not in German #1 singles.
A song that peaks below #1 on the german charts is also a song that is not the #1 single in Germany. | ∃x (Song(x) ∧ By(x, boneym,) ∧ Number1GermanSingle(x))
Song(hoorayHoorayItsAHoliHoliday) ∧ HitAllOverEurope(hoorayHoorayItsAHoliHoliday)
Song(hoorayHoorayItsAHoliHoliday) ∧ ¬Number1GermanSingle(hoorayHoorayItsAHoliHoliday)
∀x (PeakBelowOn(x, number1, germanChart) → ¬Number1GermanSingle(x)) | "Hooray! Hooray! It's a Holi-Holiday!" peaked at #3 on the UK charts. | PeaksAtOn(hoorayHoorayItsAHoliHoliday, number3, germanChart) | Uncertain |
Every chef can cook.
Some people who aren’t chefs can cook.
People who cook can make scrambled eggs and pasta.
If someone can make cookies and muffins, they are a baker.
Bakers who can also make scrambled eggs can make a good breakfast.
Luke can make cookies, scrambled eggs, and muffins, but not pasta. | ∀x (Chef(x) → Can(x, cook))
∃x (¬Chef(x) ∧ Can(x, cook))
∀x (Can(x, cook) → (CanMake(x, scrambledEggs) ∧ CanMake(x, pasta)))
∀x (CanMake(x, cookies) ∧ CanMake(x, muffins) → Baker(x))
∀x ((Baker(x) ∧ CanMake(x, scrambledEggs)) → CanMake(x, goodBreakfast))
CanMake(luke, cookies) ∧ (CanMake(luke, scrambledEggs) ∧ CanMake(... | Luke can make a good breakfast. | CanMake(luke, goodBreakfast) | True |
Every chef can cook.
Some people who aren’t chefs can cook.
People who cook can make scrambled eggs and pasta.
If someone can make cookies and muffins, they are a baker.
Bakers who can also make scrambled eggs can make a good breakfast.
Luke can make cookies, scrambled eggs, and muffins, but not pasta. | ∀x (Chef(x) → Can(x, cook))
∃x (¬Chef(x) ∧ Can(x, cook))
∀x (Can(x, cook) → (CanMake(x, scrambledEggs) ∧ CanMake(x, pasta)))
∀x (CanMake(x, cookies) ∧ CanMake(x, muffins) → Baker(x))
∀x ((Baker(x) ∧ CanMake(x, scrambledEggs)) → CanMake(x, goodBreakfast))
CanMake(luke, cookies) ∧ (CanMake(luke, scrambledEggs) ∧ CanMake(... | Luke is a chef. | Chef(luke) | False |
ETS develops various standardized tests primarily in the United States for K-12 and higher education.
ETS administers international tests, including the TOEFL, TOEIC, GRE, and subject tests.
Many of the assessments ETS develops are associated with entry to the US tertiary and quaternary education institutions.
ETS al... | ∃x ∃y (Develop(eTS, x) ∧ Develop(eTS, y) ∧ StandardizedTest(x) ∧ StandardizedTest(y) ∧ In(x, unitedState) ∧ In(y, unitedState) ∧ For(x, k12AndHigherEducation) ∧ For(y, k12AndHigherEducation))
∃x (Administer(eTS, x) ∧ InternationalTest(x) ∧ (TOEFL(x) ∨ TOEIC(x) ∨ GRE(x) ∨ SubjectTest(x)))
∃x (Develop(eTS, x) ∧ Associate... | ETS develops assessments for K-12 statewide as well as entry to US tertiary and quaternary education institutions. | ∃x ∃y (Develop(eTS, x) ∧ StateWideAssesment(x) ∧ Develop(eTS, y) ∧ AssociatedWith(y, entryToUSEducationInstitution)) | True |
ETS develops various standardized tests primarily in the United States for K-12 and higher education.
ETS administers international tests, including the TOEFL, TOEIC, GRE, and subject tests.
Many of the assessments ETS develops are associated with entry to the US tertiary and quaternary education institutions.
ETS al... | ∃x ∃y (Develop(eTS, x) ∧ Develop(eTS, y) ∧ StandardizedTest(x) ∧ StandardizedTest(y) ∧ In(x, unitedState) ∧ In(y, unitedState) ∧ For(x, k12AndHigherEducation) ∧ For(y, k12AndHigherEducation))
∃x (Administer(eTS, x) ∧ InternationalTest(x) ∧ (TOEFL(x) ∨ TOEIC(x) ∨ GRE(x) ∨ SubjectTest(x)))
∃x (Develop(eTS, x) ∧ Associate... | ETS administers international tests including the TOEFL, GRE and subject tests in China. | ∃x (Administer(eTS, x) ∧ InChina(x) ∧ (TOEFL(x) ∨ TOEIC(x) ∨ GRE(x) ∨ SubjectTest(x))) | Uncertain |
All hodophiles who enjoy eating gelato ice cream would enjoy a vacation to Italy.
No hodophiles can resist the hallmark delectable desserts famous in Italy.
Hodophiles enjoy eating gelato ice cream or love to travel and vacation often, or both.
No hodophiles who study abroad in Europe regret their college experiences.
... | ∀x (Hodophiles(x) ∧ EnjoyEating(x, gelato) → Enjoy(x, vacationToItaly))
∀x ∀y (Hodophiles(x) ∧ ¬(∃y (Resist(x, y) ∧ Hallmark(y) ∧ Delectabl(y) ∧ Dessert(y) ∧ FamousIn(y, italy))))
∀x (Hodophiles(x) → (EnjoyEating(x, gelato) ∨ LoveToTravelOften(x)))
∀x (Hodophiles(x) ∧ TakeIn(x, studyAbroadSemester, europe) → ¬Regret(x,... | Robert can resist the hallmark delectable desserts that are famous in Italy. | ∃y (Resist(robert, y) ∧ Hallmark(y) ∧ Delectabl(y) ∧ Dessert(y) ∧ FamousIn(y, italy)) | False |
To have the authorization to study in the United States as a foreigner, you must be enrolled in an academic program.
Those who are enrolled in an academic program can not work full-time.
Every who studies in the United States as a foreigner has the authorization to study in the U.S.
All PhD graduate can work full-time.... | ∀x (Have(x, authorization, studyIn, unitedStates) → EnrolledIn(x, academicProgram))
∀x (EnrolledIn(x, academicProgram) → ¬Work(x, fullTime))
∀x (StudyIn(x, unitedStates) → Have(x, authorization, studyIn, unitedStates))
∀x (PhDGraduate(x) → Work(x, fullTime))
¬StudyIn(x, unitedStates) → EnrolledIn(x, academicProgram) | Tom wants to study abroad. | StudyIn(tom, unitedStates) | Uncertain |
Islip Speedway is the smallest race track.
There was a demolition derby on the smallest race track.
Islip is either demolished or still being used.
Speedways that are still being used have races held at them.
Islip doesn't have races held at it. | Speedway(islip) ∧ SmallestRaceTrack(islip)
∃x ∃y (DemolitionDerby(x) ∧ SmallestRaceTrack(y) ∧ On(x, y))
Demolished(islip) ⊕ StillUsed(islip)
∀x (Speedway(x) ∧ StillUsed(x) → Have(races, heldAt, x))
¬Have(races, heldAt, islip) | Islip was demolished. | Demolished(islip) | True |
Islip Speedway is the smallest race track.
There was a demolition derby on the smallest race track.
Islip is either demolished or still being used.
Speedways that are still being used have races held at them.
Islip doesn't have races held at it. | Speedway(islip) ∧ SmallestRaceTrack(islip)
∃x ∃y (DemolitionDerby(x) ∧ SmallestRaceTrack(y) ∧ On(x, y))
Demolished(islip) ⊕ StillUsed(islip)
∀x (Speedway(x) ∧ StillUsed(x) → Have(races, heldAt, x))
¬Have(races, heldAt, islip) | Islip is still being used. | StillUsed(islip) | False |
If a person pays their taxes, then they contribute to the country.
Everyone who works for a government department pays a tax on their salary.
Everyone in the army is an employee of a government department.
Everyone convicted of murder goes to prison.
Everyone who has been to prison has a criminal record.
James was e... | ∀x (Taxpayer(x) → ContributeTo(x, country))
∀x (WorkFor(x, governmentAgency) → Taxpayer(x))
∀x (ServesIn(x, theArmy) → WorkFor(x, governmentAgency))
∀x (SentencedForMurder(x) → Imprisoned(x))
∀x (Imprisoned((x) → Has(x, criminalRecord)))
SentencedForMurder(james) ⊕ Imprisoned(james)
Has(james, criminalRecord) ⊕ Taxpaye... | James contributes to the country. | ContributeToCountry(james) | Uncertain |
If a person pays their taxes, then they contribute to the country.
Everyone who works for a government department pays a tax on their salary.
Everyone in the army is an employee of a government department.
Everyone convicted of murder goes to prison.
Everyone who has been to prison has a criminal record.
James was e... | ∀x (Taxpayer(x) → ContributeTo(x, country))
∀x (WorkFor(x, governmentAgency) → Taxpayer(x))
∀x (ServesIn(x, theArmy) → WorkFor(x, governmentAgency))
∀x (SentencedForMurder(x) → Imprisoned(x))
∀x (Imprisoned((x) → Has(x, criminalRecord)))
SentencedForMurder(james) ⊕ Imprisoned(james)
Has(james, criminalRecord) ⊕ Taxpaye... | James does not contribute to the country. | ¬ContributeTo(james, country) | Uncertain |
The Croton River watershed is the drainage basin of the Croton River.
The Croton River is in southwestern New York.
Water from the Croton River watershed flows to the Bronx.
The Bronx is in New York. | DrainageBasinOf(crotonRiverWatershed, crotonRiver)
In(crotonRiver, southwesternNewYork)
∀x ((Water(x) ∧ In(x, crotonRiverWatershed)) → FlowsTo(x, bronx))
In(bronx, newYork) | The Croton River watershed is in the Bronx. | In(crotonRiverWatershed, bronx) | Uncertain |
The Croton River watershed is the drainage basin of the Croton River.
The Croton River is in southwestern New York.
Water from the Croton River watershed flows to the Bronx.
The Bronx is in New York. | DrainageBasinOf(crotonRiverWatershed, crotonRiver)
In(crotonRiver, southwesternNewYork)
∀x ((Water(x) ∧ In(x, crotonRiverWatershed)) → FlowsTo(x, bronx))
In(bronx, newYork) | Water from the Croton River flows to the Bronx. | ∀x (Water(x) ∧ From(x, crotonRiver) → FlowsTo(x, bronx)) | Uncertain |
All nuclear-powered submarines are warships.
No nuclear-powered submarines are commercial vessels. | ∀x (NuclearPoweredSubmarine(x) → Warship(x))
∀x (NuclearPoweredSubmarine(x) → ¬CommercialVessel(x)) | No warships are commercial vessels. | ∀x (Warship(x) → ¬CommercialVessel(x)) | Uncertain |
If an album is written by a rock band, then the genre of the album is rock.
If a band writes an album winning an award, then this band wins this award.
Trouble at the Henhouse is an album by The Tragically Hip.
The Tragically Hip is a Canadian rock band.
The song "Butts Wigglin'" is in Trouble at the Henhouse.
Trouble ... | ∀x ∀y ∀z (AlbumByBand(x, y) ∧ RockBand(y, z) → Genre(x, rock))
∀x ∀y ∀z (AlbumByBand(x, y) ∧ AlbumAward(x, z) → RockBandAward(y, z))
AlbumByBand(trouble_at_the_Henhouse, the_Tragically_Hip)
RockBand(the_Tragically_Hip, canada)
SongInAlbum(butts_Wigglin, trouble_at_the_Henhouse)
AlbumAward(trouble_at_the_Henhouse, the_A... | "Butts Wigglin'" appeared in a film. | SongInFilm(buttsWigglin) | Uncertain |
Daniel is a software engineer, and he works at Palantir Technologies.
Daniel studied bioengineering during his undergraduate at Rice University.
Daniel’s older sister works at Meta as a technical sourcer.
Daniel’s dad and older sister both graduated from Stanford University.
Daniel’s dad is a doctor practicing interna... | SoftwareEngineer(daniel) ∧ WorksAt(daniel, palantirTechnologies)
Studied(daniel, bioengineering) ∧ UndergraduateAt(daniel, riceUniversity)
WorksAtMeta(danielsOlderSister) ∧ TechnicalSourcer(danielsOlderSister)
GraduatedFromStanfordUniversity(danielsOlderSister) ∧ GraduatedFromStanfordUniversity(danielsDad)
Doctor(danie... | Daniel once applied to Stanford University, but he couldn’t get in even though he has family members who are Stanford alumni. | AppliedTo(daniel, stanfordUniversity) ∧ ¬GotInto(daniel, stanfordUniversity) ∧ Alumni(danielsFamilyMembers, stanfordUniversity) | Uncertain |
Daniel is a software engineer, and he works at Palantir Technologies.
Daniel studied bioengineering during his undergraduate at Rice University.
Daniel’s older sister works at Meta as a technical sourcer.
Daniel’s dad and older sister both graduated from Stanford University.
Daniel’s dad is a doctor practicing interna... | SoftwareEngineer(daniel) ∧ WorksAt(daniel, palantirTechnologies)
Studied(daniel, bioengineering) ∧ UndergraduateAt(daniel, riceUniversity)
WorksAtMeta(danielsOlderSister) ∧ TechnicalSourcer(danielsOlderSister)
GraduatedFromStanfordUniversity(danielsOlderSister) ∧ GraduatedFromStanfordUniversity(danielsDad)
Doctor(danie... | Daniel studied bioengineering as an undergraduate at Rice University. | Studied(daniel, bioengineering) ∧ UndergraduateAt(daniel, riceUniversity) | True |
Daniel is a software engineer, and he works at Palantir Technologies.
Daniel studied bioengineering during his undergraduate at Rice University.
Daniel’s older sister works at Meta as a technical sourcer.
Daniel’s dad and older sister both graduated from Stanford University.
Daniel’s dad is a doctor practicing interna... | SoftwareEngineer(daniel) ∧ WorksAt(daniel, palantirTechnologies)
Studied(daniel, bioengineering) ∧ UndergraduateAt(daniel, riceUniversity)
WorksAtMeta(danielsOlderSister) ∧ TechnicalSourcer(danielsOlderSister)
GraduatedFromStanfordUniversity(danielsOlderSister) ∧ GraduatedFromStanfordUniversity(danielsDad)
Doctor(danie... | Daniel and his sister grew up in Minneapolis, Minnesota. | GrewUpIn(daniel, minneapolis) ∧ GrewUpIn(danielsOlderSister, minneapolis) | Uncertain |
The world's only major large passenger aircraft manufacturers are Boeing and Airbus.
All American Airlines planes are from the world's major large passenger aircraft manufacturers.
Airbus made more revenue than Boeing last year. | ∀x (WorldMajorLargePassengerAircraftManufacturer(x) → x=boeing ⊕ x=airbus)
∀x (AmericanAirlinesAircraft(x) → WorldMajorLargePassengerAircraftManufacturer(x))
MoreInRevenue(airbus, boeing) | An American Airlines plane is either a Boeing or Airbus plane. | ∀x (AmericanAirlinesPlane(x) → x=boeing ⊕ x=airbus) | True |
The world's only major large passenger aircraft manufacturers are Boeing and Airbus.
All American Airlines planes are from the world's major large passenger aircraft manufacturers.
Airbus made more revenue than Boeing last year. | ∀x (WorldMajorLargePassengerAircraftManufacturer(x) → x=boeing ⊕ x=airbus)
∀x (AmericanAirlinesAircraft(x) → WorldMajorLargePassengerAircraftManufacturer(x))
MoreInRevenue(airbus, boeing) | There exists a SpaceX commercial aircraft. | ∃x (CommercialAircraft(x) ∧ x=spaceX) | Uncertain |
The world's only major large passenger aircraft manufacturers are Boeing and Airbus.
All American Airlines planes are from the world's major large passenger aircraft manufacturers.
Airbus made more revenue than Boeing last year. | ∀x (WorldMajorLargePassengerAircraftManufacturer(x) → x=boeing ⊕ x=airbus)
∀x (AmericanAirlinesAircraft(x) → WorldMajorLargePassengerAircraftManufacturer(x))
MoreInRevenue(airbus, boeing) | There does not exist a United Airlines plane produced by Boeing. | ∀x (UnitedAirlinesAircraft(x) → ¬(x=boeing)) | Uncertain |
Luzon is an island in the Philippines.
In December 1999, an earthquake struck Luzon.
People died in the December 1999 earthquake in Luzon. | Island(luzon) ∧ In(luzon, philippines)
∃x (Earthquake(x) ∧ StrikeInYr(x, year1999) ∧ StrikeInMo(x, december) ∧ StrikeInCity(x, luzon))
∃x (Earthquake(x) ∧ StrikeInYr(x, year1999) ∧ StrikeInMo(x, december) ∧ StrikeInCity(x, luzon) ∧ Deadly(x)) | Leyte is an island in the Philippines. | Island(leyte) ∧ In(leyte, philippines) | Uncertain |
Luzon is an island in the Philippines.
In December 1999, an earthquake struck Luzon.
People died in the December 1999 earthquake in Luzon. | Island(luzon) ∧ In(luzon, philippines)
∃x (Earthquake(x) ∧ StrikeInYr(x, year1999) ∧ StrikeInMo(x, december) ∧ StrikeInCity(x, luzon))
∃x (Earthquake(x) ∧ StrikeInYr(x, year1999) ∧ StrikeInMo(x, december) ∧ StrikeInCity(x, luzon) ∧ Deadly(x)) | In 1999, there was at least one earthquake in the Philippines. | ∃x ∃y (Earthquake(x) ∧ StrikeInYr(x, year1999) ∧ StrikeInMo(x, december) ∧ StrikeInCity(x, y) ∧ In(y, philippines)) | True |
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