prajaktakini/folio huggingface dataset:
Premises:
All people who went to Clay's school and who make their own matcha teas every morning with ceremonial-grade matcha powder do not wake up late and start their schedules past noon regularly.
All people who went to Clay's school, who live in California, and attend yoga classes regularly, make their own matcha teas every morning with ceremonial-grade matcha powder.
All people who went to Clay's school, and work in the entertainment industry as high-profile celebrities, wake up late and start their schedules past noon regularly.
All people who went to Clay's school that do not have regular 9-5 jobs, work in the entertainment industry as high-profile celebrities.
All people who went to Clay's school and prefer working at home over going to the office daily do not have regular 9-5 jobs.
Bunny went to Clay's school, and she either prefers to work at home over going to the office and makes her own matcha teas every morning with ceremonial-grade matcha powder, or does not prefer to work at home over going to the office every day and does not make her own matcha teas every morning with ceremonial-grade matcha powder.
Premises (first-order logic):
∀x (GoTo(x, claysSchool) ∧ MakeWith(x, theirOwnMatchTea, ceremonialGradePowder) → ¬(WakeUpLate(x) ∧ StartPastNoonRegularly(x, schedule)))
∀x (GoTo(x, claysSchool) ∧ LiveIn(x, california) ∧ AttendRegularly(x, yogaClass) → MakeWith(x, ownMatch, ceremonialGradePowder))
∀x (GoTo(x, claysSchool) ∧ WorkInAs(x, entertainmentIndustry, highProfileCelebrity) → (WakeUpLate(x) ∧ StartPastNoonRegularly(x, schedule)))
∀x (GoTo(x, claysSchool) ∧ ¬(Have(x, y) ∧ Regular(y) ∧ NineToFiveJob(y)) → WorkInAs(x, entertainmentIndustry, highProfileCelebrity))
∀x (GoTo(x, claysSchool) ∧ Prefer(x, workingAtHome, goingToTheOffice) → ¬(Have(x, y) ∧ Regular(y) ∧ NineToFiveJob(y)))
GoTo(bunny, claysSchool) ∧ ¬(Prefer(bunny, workingAtHome, goingToTheOffice) ⊕ MakeWith(bunny, theirOwnMatchTea, ceremonialGradePowder))

Conclusion: Bunny does not have a regular 9-5 job.
Conclusion (first-order logic): Have(bunny, y) ∧ Regular(y) ∧ NineToFiveJob(y)
Label: Uncertain
Premises:
Thomas Barber was an English professional footballer.
Thomas Barber played in the Football League for Aston Villa.
Thomas Barber played as a halfback and inside left.
Thomas Barber scored the winning goal in the 1913 FA Cup Final.
Premises (first-order logic):
English(thomasBarber) ∧ ProfessionalFootballer(thomasBarber)
PlayedFor(thomasBarber, astonVilla) ∧ PlayedIn(astonVilla,theFootballLeague)
PlayedAs(thomasBarber, halfBack) ∧ PlayedAs(thomasBarber, insideLeft)
ScoredTheWinningGoalIn(thomasBarber, facupfinal1913)

Conclusion: Thomas Barber played in the Football League for Bolton Wanderers
Conclusion (first-order logic): PlayedFor(thomasBarber, boltonWanderers) ∧ PlayedIn(boltonWanderers,theFootballLeague)
Label: Uncertain

Conclusion: Thomas Barber played as an inside left.
Conclusion (first-order logic): PlayedAs(thomasBarber, insideLeft)
Label: True

Conclusion: An English professional footballer scored the winning goal in the 1913 FA Cup Final.
Conclusion (first-order logic): ∃x (English(x) ∧ ProfessionalFootballer(x) ∧ ScoredTheWinningGoalIn(x, facupfinal1913))
Label: True
Premises:
If a person plays an instrument in a concert, they are good at playing this kind of instrument.
Peter plays piano, violin, and saxophone.
Peter plays piano in a concert.
Oliver and Peter both play instruments in a concert.
Oliver plays a different musical instrument from Peter in the concert.
Premises (first-order logic):
∀x ∀y (PlayIn(y, x, concert) → GoodAtPlaying(y, x))
Play(peter, piano) ∧ Play(peter, violin) ∧ Play(peter, saxophone)
PlayIn(peter, piano, concert)
∃x ∃y (PlayIn(peter, x, concert) ∧ PlayIn(oliver, y, concert))
∀x (PlayIn(oliver, x, concert) → ¬PlayIn(peter, y, concert))

Conclusion: Peter is good at playing piano.
Conclusion (first-order logic): GoodAtPlaying(peter, piano)
Label: True
Premises:
Cancer biology is finding genetic alterations that confer a selective advantage to cancer cells.
Cancer researchers have frequently ranked the importance of substitutions to cancer growth by the P value.
P values are thresholds for belief, not metrics of effect.
Premises (first-order logic):
Finding(cancerBiology, geneticAlteration) ∧ Confer(geneticAlteration, selectiveAdvantage, toCancerCell)
∃x ∃y (CancerResearcher(x) ∧ Ranked(x, importanceOfSubstitutionsToCancerGrowth) ∧ PValue(y) ∧ RankedBy(importanceOfSubstitutionsToCancerGrowth, y))
∀x (PValue(x) → ThresholdForBelief(x) ∧ ¬MetricOfEffect(x))

Conclusion: Cancer researchers tend to use the cancer effect size to determine the relative importance of the genetic alterations that confer selective advantage to cancer cells.
Conclusion (first-order logic): ∃x ∃y (CancerResearcher(x) ∧ Use(x, cancerEffectSize) ∧ UsedToDetermine(cancerEffectSize, relativeImportanceOfGeneteticAlterations))
Label: Uncertain

Conclusion: P value represents the selection intensity for somatic variants in cancer cell lineages.
Conclusion (first-order logic): SelectionIntensitySomaticVariants(pValue)
Label: Uncertain

Conclusion: Cancer effect size is preferred by cancer researchers.
Conclusion (first-order logic): Preferred(cancerResearchers, cancerEffectSize)
Label: Uncertain
Premises:
All biodegradable things are environment-friendly.
All woodware is biodegradable.
All paper is woodware.
Nothing is a good thing and also a bad thing.
All environment-friendly things are good.
A worksheet is either paper or environment-friendly.
Premises (first-order logic):
∀x (Biodegradable(x) → EnvironmentFriendly(x))
∀x (Woodware(x) → Biodegradable(x))
∀x (Paper(x) → Woodware(x))
¬(∃x (Good(x) ∧ Bad(x)))
∀x (EnvironmentFriendly(x) → Good(x))
Paper(worksheet) ⊕ EnvironmentFriendly(worksheet)

Conclusion: A worksheet is biodegradable.
Conclusion (first-order logic): Bioegradable(worksheet)
Label: Uncertain

Conclusion: A worksheet is not biodegradable.
Conclusion (first-order logic): ¬Bioegradable(worksheet)
Label: Uncertain

Conclusion: A worksheet is bad.
Conclusion (first-order logic): Bad(worksheet)
Label: False

Conclusion: A worksheet is not bad.
Conclusion (first-order logic): ¬Bad(worksheet)
Label: True
Premises:
No reptile has fur.
All snakes are reptiles.
Premises (first-order logic):
∀x (Reptile(x) → ¬Have(x, fur))
∀x (Snake(x) → Reptile(x))

Conclusion: Some snake has fur.
Conclusion (first-order logic): ∃x (Snake(x) ∧ Have(x, fur))
Label: False
Premises:
All buildings in New Haven are not high.
All buildings managed by Yale Housing are located in New Haven.
All buildings in Manhattans are high.
All buildings owned by Bloomberg are located in Manhattans.
All buildings with the Bloomberg logo are owned by Bloomberg.
Tower A is managed by Yale Housing.
Tower B is with the Bloomberg logo.
Premises (first-order logic):
∀x (In(x, newHaven) → ¬High(x))
∀x (YaleHousing(x) → In(x, newHaven))
∀x (In(x, manhattan) → High(x))
∀x (Bloomberg(x) → In(x, manhattan))
∀x (BloombergLogo(x) → Bloomberg(x))
YaleHousing(tower-a)
BloombergLogo(tower-b)

Conclusion: Tower A is low.
Conclusion (first-order logic): ¬High(tower-a)
Label: True

Conclusion: Tower B is not located in Manhattans.
Conclusion (first-order logic): ¬In(tower-b, manhattan)
Label: False
Premises:
No birds are ectothermic.
All penguins are birds.
An animal is ectothermic or endothermic.
All endothermic animals produce heat within the body.
Ron and Henry are both animals.
Ron is not a bird and does not produce heat with the body.
Henry is not a cat and does not produce heat with the body.
Premises (first-order logic):
∀x (Bird(x) → ¬Ectothermic(x))
∀x (Penguin(x) → Bird(x))
∀x (Animal(x) → Ectothermic(x) ∨ Endothermic(x))
∀x (Endothermic(x) → ProduceWithIn(x, heat, body))
Animal(ron) ∧ Animal(henry)
¬Bird(ron) ∧ ¬ProduceWithIn(ron, heat, body)
¬Cat(henry) ∧ ¬ProduceWithIn(henry, heat, body)

Conclusion: Ron is a cat.
Conclusion (first-order logic): Cat(ron)
Label: Uncertain

Conclusion: Either Henry is a penguin or Henry is endothermic.
Conclusion (first-order logic): Penguin(henry) ⊕ Endothermic(henry)
Label: False

Conclusion: Ron is either both a penguin and endothermic, or he is nether.
Conclusion (first-order logic): ¬(Penguin(ron) ⊕ Endothermic(henry))
Label: True
Premises:
Ambiortus is a prehistoric bird genus.
Ambiortus Dementjevi is the only known species of Ambiortus.
Mongolia was where Ambiortus Dementjevi lived.
Yevgeny Kurochkin was the discoverer of Ambiortus.
Premises (first-order logic):
Prehistoric(ambiortus) ∧ BirdGenus(ambiortus)
∀x(KnownSpeciesOf(x, ambiortus) → IsSpecies(x, ambiortusDementjevi))
LiveIn(ambiortusDementjevi, mongolia)
Discover(yevgenykurochkin, ambiortus)

Conclusion: Yevgeny Kurochkin discovered a new bird genus.
Conclusion (first-order logic): ∃x (Discover(yevgenykurochkin, x) ∧ BirdGenus(x))
Label: True

Conclusion: Yevgeny Kurochkin lived in Mongolia.
Conclusion (first-order logic): LiveIn(yevgenykurochkin, mongolia)
Label: Uncertain
Premises:
Everyone that knows about breath-first-search knows how to use a queue.
If someone is a seasoned software engineer interviewer at Google, then they know what breath-first-search is.
Someone is either a seasoned software engineer interviewer at Google, has human rights, or both.
Every person who has human rights is entitled to the right to life and liberty.
Everyone that knows how to use a queue knows about the first-in-first-out data structure.
Everyone that is entitled to the right to life and liberty cannot be deprived of their rights without due process of law.
Jack is entitled to the right to life and liberty, has human rights, or knows about the first-in-first-out data structure.
Premises (first-order logic):
∀x (Know(x, breathFirstSearch) → Know(x, howToUseQueue))
∀x (Seasoned(x) ∧ SoftwareEngineerInterviewer(x) ∧ At(x, google) → Know(x, breathFirstSearch))
∀x ((Seasoned(x) ∧ SoftwareEngineerInterviewer(x) ∧ At(x, google)) ∨ Have(x, humanRights))
∀x (Have(x, humanRights) → EntitledTo(x, rightToLifeAndLiberty))
∀x (Know(x, howToUseQueue) → Know(x, firstInFirstOutDataStructure))
∀x (EntitledTo(x, rightToLifeAndLiberty) → ¬DeprivedOfWithout(x, rights, dueProcessOfLaw))
(EntitledTo(jack, rightToLifeAndLiberty) ∨ Have(jack, humanRights) ∨ Know(jack, firstInFirstOutDataStructure))

Conclusion: Jack is a seasoned software engineer interviewer.
Conclusion (first-order logic): Seasoned(jack) ∧ SoftwareEngineerInterviewer(jack) ∧ At(jack, google)
Label: Uncertain
Premises:
Fort Ticonderoga is the current name for Fort Carillon.
Pierre de Rigaud de Vaudreuil built Fort Carillon.
Fort Carillon was located in New France.
New France is not in Europe.
Premises (first-order logic):
RenamedAs(fortCarillon, fortTiconderoga)
Built(pierredeRigauddeVaudreuil, fortCarillon)
LocatedIn(fortCarillon, newFrance)
¬LocatedIn(newFrance, europe)

Conclusion: Pierre de Rigaud de Vaudreuil built a fort in New France.
Conclusion (first-order logic): ∃x (Built(pierredeRigauddeVaudreuil, x) ∧ LocatedIn(x, newFrance))
Label: True

Conclusion: Pierre de Rigaud de Vaudreuil built a fort in New England.
Conclusion (first-order logic): ∃x (Built(pierredeRigauddeVaudreuil, x) ∧ LocatedIn(x, newEngland))
Label: Uncertain

Conclusion: Fort Carillon was located in Europe.
Conclusion (first-order logic): LocatedIn(fortCarillon, europe)
Label: Uncertain
Premises:
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.
Premises (first-order logic):
∀x (ProfessionalSoccerPlayer(x) → ¬ProfessionalBasketballPlayer(x))
∀x (NBAPlayer(x) → ProfessionalBasketballPlayer(x))
∀x (ProfessionalSoccerDefender(x) → ProfessionalSoccerPlayer(x))
∀x (ProfessionalCenterback(x) → ProfessionalSoccerDefender(x))
(NBAPlayer(stephencurry) ⊕ ProfessionalSoccerPlayer(stephencurry)) → ProfessionalBasketballPlayer(stephencurry)

Conclusion: Stephen Curry is an NBA player.
Conclusion (first-order logic): NBAPlayer(stephenCurry)
Label: Uncertain
Premises:
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.
Premises (first-order logic):
∀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)

Conclusion: Inception is a folk song.
Conclusion (first-order logic): FolkSong(inception)
Label: False

Conclusion: Inception is not a folk song.
Conclusion (first-order logic): ¬FolkSong(inception)
Label: True

Conclusion: Inception is either a video or a folk song.
Conclusion (first-order logic): Video(inception) ⊕ FolkSong(inception)
Label: True

Conclusion: Mac is a video.
Conclusion (first-order logic): Video(mac)
Label: Uncertain
Premises:
No plants are fungi.
Mushrooms are fungi.
Premises (first-order logic):
∀x (Plant(x) → ¬Fungi(x))
∀x (Mushroom(x) → Fungi(x))

Conclusion: No plants are mushrooms.
Conclusion (first-order logic): ∀x (Plant(x) → ¬Mushroom(x))
Label: True
Premises:
No road is dustless.
Some streets are roads.
Premises (first-order logic):
∀x (Road(x) → ¬Dustless(x))
∃x ∃y (Street(x) ∧ Street(y) ∧ Road(x) ∧ Road(y) ∧ ¬(x=y))

Conclusion: Some streets are dustless.
Conclusion (first-order logic): ∃x ∃y (Street(x) ∧ Street(y) ∧ Dustless(x) ∧ Dustless(y) ∧ ¬(x=y))
Label: Uncertain
Premises:
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.
Premises (first-order logic):
∀x (Musician(x) → Have(x, busyLife))
Musician(singhKaur) ∧ Famous(singhKaur)
∀x (Musician(x) ∧ ¬Famous(x) → ¬MakeALotOfMoney(x))
∃x (Musician(x) ∧ (Singer(x) ∨ Writer(x)))

Conclusion: Singh Kaur makes a lot of money.
Conclusion (first-order logic): MakeALotOfMoney(singhKaur)
Label: Uncertain

Conclusion: Singh Kaur is a writer.
Conclusion (first-order logic): Writer(singhKaur)
Label: Uncertain

Conclusion: Singh Kaur has a very busy life.
Conclusion (first-order logic): Have(singhKaur, busyLife)
Label: True
Premises:
Each building is tall.
Everything tall has height.
Premises (first-order logic):
∀x (Building(x) → Tall(x))
∀x (Tall(x) → Height(x))

Conclusion: All buildings are magnificent.
Conclusion (first-order logic): ∀x (Building(x) → Magnificent(x))
Label: Uncertain
Premises:
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.
Premises (first-order logic):
∀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(controlledSubstancesAct)
∃x ∃y(Act(x) ∧ PreventsHarm(x) ∧ (¬(x=y)) ∧ Act(y) ∧ PreventsHarm(y))

Conclusion: The Controlled Substances Act prevents harmful things.
Conclusion (first-order logic): PreventsHarm(controlledSubstancesAct)
Label: Uncertain

Conclusion: A child in chemical endangerment is in harm.
Conclusion (first-order logic): ∀x ((Child(x) ∧ InChemicalEndangerment(x)) → Harmful(x))
Label: True
Premises:
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 entrepreneur nor a person who hates working for others, then Mark Zuckerberg is not a risk-averse working person.
Premises (first-order logic):
∀x (Have(x, corporateJob) → ¬Take(x, financialRisk))
∀x (Entrepreneur(x) → Take(x, financialRisk))
∀x (RiskAverse(x) → Have(x, corporateJob))
∀x (∃y ∃z (¬(y=x) ∧ ¬(z=x) ∧ ¬(y=z) ∧ HateWorkingFor(x, y) ∧ HateWorkingFor(x, z)) → Entrepreneur(x))
¬Entrepreneur(markZuckerberg) ∧ ¬(∃y ∃z (¬(y=markZuckerberg) ∧ ¬(z=markZuckerberg) ∧ ¬(y=z) ∧ HateWorkingFor(markZuckerberg, y) ∧ HateWorkingFor(markZuckerberg, z))) → ¬RiskAverse(markZuckerberg)

Conclusion: Mark Zuckerberg is an entrepreneur.
Conclusion (first-order logic): Entrepreneur(markZuckerberg)
Label: Uncertain

Conclusion: Mark Zuckerberg is a risk-averse person.
Conclusion (first-order logic): RiskAverse(markZuckerberg)
Label: False

Conclusion: Mark Zuckerberg is not a risk-averse person.
Conclusion (first-order logic): ¬RiskAverse(markZuckerberg)
Label: True
Premises:
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.
Premises (first-order logic):
∃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))

Conclusion: Some wildfeed is violating copyright laws.
Conclusion (first-order logic): ∃x (Wildfeed(x) ∧ CopyrightViolation(x))
Label: True

Conclusion: Wildfeed can be prerecorded.
Conclusion (first-order logic): ∃x (Wildfeed(x) ∧ Prerecorded(x))
Label: True

Conclusion: Syndicated shows are copyright violations.
Conclusion (first-order logic): ∃x (SyndicatedShows(x) ∧ CopyrightViolation(x))
Label: Uncertain
Premises:
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.
Premises (first-order logic):
Poem(catullus4) ∧ WrittenBy(catullus4, catullus) ∧ AncientRomanWriter(catullus)
Story(catullus4) ∧ About(catullus4, retirementOfAWellTraveledShip)
Poem(catullus4) ∧ StrongAgingAnalogy(catullus4)
Poem(catullus4) ∧ WrittenIn(catullus4, iambicTrimeter) ∧ Convey(catullus4, aSenseOfSpeedOverTheWaves)

Conclusion: Callus 4 is written in an unusual iambic trimeter to convey a strong analogy of human aging.
Conclusion (first-order logic): Poem(catullus4) ∧ WrittenIn(catullus4, iambicTrimeter) ∧ StrongAgingAnalogy(catullus4)
Label: True
Premises:
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 human visitors.
Premises (first-order logic):
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, malfunctioningRobots)

Conclusion: Michael Crichton has directed a film about malfunctioning robots.
Conclusion (first-order logic): ∃x (Film(x) ∧ Directed(michael, x) ∧ About(x, malfunctioningRobots))
Label: True
Premises:
Xiufeng, Xiangshan, Diecai, Qixing are districts in the city of Guilin.
Yangshuo is not a district in Guilin.
Premises (first-order logic):
DistrictIn(xiufeng, guilin) ∧ DistrictIn(xiangshan, guilin) ∧ DistrictIn(diecai, guilin) ∧ DistrictIn(qixing, guilin) ∧ City(guilin)
¬DistrictIn(yangshuo, guilin)

Conclusion: Xiangshan and Diecai are districts in the same city.
Conclusion (first-order logic): ∃x (DistrictIn(xiangshan, x) ∧ DistrictIn(diecai, x) ∧ City(x))
Label: True

Conclusion: Xiufeng is a district in Guilin.
Conclusion (first-order logic): DistrictIn(xiufeng, guilin)
Label: True

Conclusion: Kowloon District is in Hong Kong.
Conclusion (first-order logic): DistrictIn(kowloon, hongKong)
Label: Uncertain
Premises:
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 vegetables in their home garden.
All of Michael's neighbors who enjoy going out often to restaurants with friends order takeout from delivery services often.
All of Michael's neighbors who regularly tout the benefits of homegrown and homecooked meals over fast food enjoy going out often to restaurants with friends.
Peter, Michael's neighbor, grows his own fresh vegetables in his home garden, or regularly touts the benefits of homegrown and homecooked meals over fast food, or both.
Premises (first-order logic):
∀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) → Grow(x, vegetable, garden))
∀x (MichaelsNeightbor(x) ∧ EnjoyGoingOutOftenToWith(x, restaurant, friend) → OrderOften(x, takeout))
∀x (MichaelsNeightbor(x) ∧ ToutOver(x, homecookedMeals, fastFood) → EnjoyGoingOutOftenToWith(x, restaurant, friend))
MichaelsNeightbor(peter) ∧ (GrowIn(peter, vegetable, garden) ∨ ToutOver(peter, homecookedMeals, fastFood))

Conclusion: Peter enjoys going out often to restaurants with friends.
Conclusion (first-order logic): EnjoyGoingOutOftenTo(peter, restaurant, friend)
Label: Uncertain
Premises:
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.
Premises (first-order logic):
∀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)

Conclusion: ModelXX is easy to operate.
Conclusion (first-order logic): EasyToOperate(modelXX)
Label: True

Conclusion: ModelXX is controlled by managers.
Conclusion (first-order logic): ControlledBy(modelXX, managers)
Label: Uncertain

Conclusion: ModelXX is connected to Google Home.
Conclusion (first-order logic): ConnectedTo(modelXX, googleHome)
Label: Uncertain