yuansui/folio huggingface dataset:
Premises:
All drinks on the counter are edible. 
All juices on the counter are drinks. 
Orange juice is a type of juice. 
Everything on the counter is either orange juice or apple juice.
All apple juices on the counter are sweet.
The coke is on the counter and if the coke is apple juice, then the coke is a drink.
If the coke is not apple juice, then the coke is not edible.

Premises in first-order logic:
∀x (OnCounter(x) ∧ Drink(x) → Edible(x))
∀x (OnCounter(x) ∧ Juice(x) → Drink(x))
∀x (OrangeJuice(x) → Juice(x))
∀x (OnCounter(x) → OrangeJuice(x) ⊕ AppleJuice(x))
∀x (OnCounter(x) ∧ AppleJuice(x) → Sweet(x))
OnCounter(coke) ∧ (AppleJuice(coke) → Drink(coke))
¬AppleJuice(coke) → ¬Edible(coke)

Conclusions:
The coke is orange juice.
The coke is edible and sweet.
The coke is not edible and sweet.

Conclusions in first-order logic:
OrangeJuice(coke)
Edible(coke) ∧ Sweet(coke)
¬(Edible(coke) ∧ Sweet(coke))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
F
Premises:
All children are human.
If someone is underage, then they are a child.
People are either underage or of age.
If someone is of age, then they can vote.
If someone is of age, they can legally get married.
If Jack is a child and a human, then Jack is neither able to vote nor get married.

Premises in first-order logic:
∀x (Child(x) → Human(x))
∀x (Underage(x) → Child(x)) 
∀x (Underage(x) ⊕ OfAge(x))
∀x (OfAge(x) → CanVote(x))
∀x (OfAge(x) → CanGetMarried(x))
Child(jack) ∧ Human(jack) → (¬CanVote(jack) ∧ ¬CanGetMarried(jack))

Conclusions:
Jack is a human.
Jack is able to vote and get married.
Jack is either able to vote or legally able to get married.

Conclusions in first-order logic:
Human(jack)
CanVote(jack) ∧ CanGetMarried(jack)
CanVote(jack) ⊕ CanGetMarried(jack)

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
F
Premises:
A diseases affect females or males.
No women have prostate cancer.
A cancer is either prostate cancer or non-prostate cancer. 
No type of cancer is without mutations.
All non-prostate cancers are a type of cancer.
If adenocarcinoma is a type of cancer or without mutations or both, then adenocarcinoma is in women or without mutations or both.

Premises in first-order logic:
∀x (Disease(x) → (Affects(x, female) ∨ Affects(x, male)) )
∀x (Affect(x, female) → ¬ProstateCancer(x))
∀x (ProstateCancer(x) ∨ NonProstateCancer(x)) 
∀x (Cancer(x) → ¬Without(x, mutation)) 
∀x (NonProstateCancer(x) → Cancer(x)) 
(Cancer(adenocarcinoma) ∨ Without(adenocarcinoma, mutation)) → (Affect(adenocarcinoma, female) ∨ Without(adenocarcinoma, mutation))

Conclusions:
Adenocarcinoma is a prostate cancer. 
Adenocarcinoma is a disease in women.
If adenocarcinoma is a disease in women or without mutations, then adenocarcinoma is without mutations and a non-prostate cancer.

Conclusions in first-order logic:
ProstateCancer(adenocarcinoma) 
Affect(adenocarcinoma, men) 
(Affect(adenocarcinoma, men) ∨ Without(adenocarcinoma, mutation)) → (NonProstateCancer(adenocarcinoma) ∧ Without(adenocarcinoma, mutation))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
F
Premises:
If someone is ranked highly by the Women's Tennis Association, then they are one of the most active players in major tennis. 
Everyone who lost to Iga Świątek at Roland Garros 2022 is ranked highly by the Women's Tennis Association.
All female tennis players at Roland Garros 2022 lost to Iga Świątek.
All tennis players at Roland Garros 2022 are either female or male.
All male tennis players at Roland Garros in 2022 lost to Rafael Nadal.
If Coco Gauff is ranked highly by the Women's Tennis Association or lost to Rafael Nadal, then Coco Gauff is not a male tennis player at Roland Garros 2022.
Coco Gauff is at Roland Garros 2022.

Premises in first-order logic:
∀x (RankedHighlyBy(x, womensTennisAssociation) → MostActivePlayerIn(x, majorTennis))
∀x (LostTo(x, świątek) ∧  At(x, rolandGarros2022) → RankedHighlyBy(x, womensTennisAssociation))
∀x (FemaleTennisPlayer(x) ∧ At(x, rolandGarros2022) → LostTo(x, świątek) ∧  At(x, rolandGarros2022))
∀x (TennisPlayer(x) ∧ At(x, rolandGarros2022) → (Female(x) ∧ TennisPlayer(x)) ⊕ (Male(x) ∧ TennisPlayer(x))) 
∀x (Male(x) ∧ TennisPlayer(x) ∧ At(x, rolandGarros2022) → LostTo(x, świątek) ∧ At(x, rolandGarros2022))
RankedHighlyBy(cocoGauff, womensTennisAssociation) ∨ (LostTo(cocoGauff, świątek) ∧ LostAt(cocoGauff, rolandGarros2022)) → ¬(Male(cocoGauff) ∧ TennisPlayer(cocoGauff) ∧ AtRolandGarros2022(cocoGauff))
TennisPlayer(cocoGauff) ∧ At(cocoGauff, rolandGarros2022)

Conclusions:
Coco Gauff is among the most active Grand-Slam players. 
Coco Gauff has lost to Rafael Nadal. 
Coco Gauff is not both a player who lost to Iga Świątek at Roland Garros 2022 and one of the most active players in major tennis.

Conclusions in first-order logic:
MostActivePlayerIn(cocoGauff, majorTennis) 
LostTo(cocoGauff, świątek) ∧ At(cocoGauff, rolandGarros2022)
¬(LostTo(cocoGauff, świątek) ∧ At(cocoGauff, rolandGarros2022)) ∨ ¬MostActivePlayerIn(cocoGauff, majorTennis) 

Truth value of each conclusion (T = true, F = false, U = unknown):
T
U
F
Premises:
None of the kids in our family love the opera.
All of the adults in our family love the opera.
If someone in our family is a scientist, then they are an adult.
Some students in our family are kids.
Billy is a kid in our family.

Premises in first-order logic:
∀x ((Kid(x) ∧ In(x, ourFamily)) → ¬Love(x, opera))
∀x ((Adult(x) ∧ In(x, ourFamily)) → Love(x, opera))
∀x ((Scientist(x) ∧ In(x, ourFamily)) → Adult(x))
∃x (Student(x) ∧ In(x, ourFamily) ∧ Kid(x))
Kid(billy) ∧ In(billy, ourFamily) 

Conclusions:
Billy is a student.
Billy is a student and a scientist.
If Billy is a student or a scientist, then Billy is a student and a kid.

Conclusions in first-order logic:
Student(billy)
Student(billy)  ∧ Scientist(billy)
(Student(billy) ∨ Scientist(billy)) → (Student(billy) ∧ Kid(billy))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
F
T
Premises:
If people at Mary's school work in student jobs on campus, then they need to earn money to help pay for their college tuition.
If people at Mary's school order takeout frequently in college, then they work in student jobs on campus.
People at Mary's school order takeout frequently in college or enjoy the dining hall meals and recipes.
If people at Mary's school enjoy the dining hall meals and recipes, then they are not picky eaters.
If people at Mary's school enjoy the dining hall meals and recipes, then they spend a lot of their time eating and catching up with friends in the campus dining halls.
Hannah is at Mary's school.
Hannah works in student jobs on campus and if she needs to earn money to help pay for her college tuition, then she is neither picky nor needs to earn money to help pay for her college tuition.

Premises in first-order logic:
∀x (At(x, marysSchool) ∧ WorkIn(x, studentJob, campus) → NeedToEarnMoneyToHelpPayFor(x, collegeTuition))
∀x (At(x, marysSchool) ∧ OrderFrequently(x, takeout) → WorkIn(x, studentJob, campus))
∀x (At(x, marysSchool) ∧ (OrderFrequently(x, takeout) ∨ Enjoy(x, diningHallMeal)))
∀x (At(x, marysSchool) ∧ Enjoy(x, diningHallMeal) → ¬PickyEater(x))
∀x (At(x, marysSchool) ∧ Enjoy(x, diningHallMeal) → Spend(x, aLotOfTime, eating) ∧ Spend(x, aLotOfTime, catchingUpWithFriends, diningHall))
At(hannah, marysSchool)
(WorkIn(hannah, studentJob, campus) ∧ NeedToEarnMoneyToHelpPayFor(hannah, collegeTuition) → ¬(PickyEater(hannah) ∨ NeedToEarnMoneyToHelpPayFor(hannah, collegeTuition))

Conclusions:
Hannah needs to earn money to help pay for her college tuition.
Hannah is at Mary's school and she is not a picky eater and spends a lot of her time eating and catching up with friends in the campus dining halls.
Hannah is at Mary's school and she either is not a picky eater or, if she is, then she spends a lot of her time eating and catching up with friends in the campus dining halls.

Conclusions in first-order logic:
NeedToEarnMoneyToHelpPayFor(hannah, collegeTuition)
¬(PickyEater(hannah) ∧ Spend(hannah, aLotOfTime, eating) ∧ Spend(hannah, aLotOfTime, catchingUpWithFriends, diningHall))
PickyEater(hannah) ⊕ (Spend(hannah, aLotOfTime, eating) ∧ Spend(hannah, aLotOfTime, catchingUpWithFriends, diningHall))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
F
Premises:
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.

Premises in first-order logic:
∀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)

Conclusions:
Jack is a thing.
Jack is not a thing.
Jack is a thing and an iPhone.
Jack is not both a thing and an iPhone.

Conclusions in first-order logic:
Thing(jack)
¬Thing(jack)
Thing(jack) ∧ Iphone(jack)
¬(Thing(jack) ∧ Iphone(jack))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
U
F
T
Premises:
All brain study designs are either block designs or event-related designs. 
All event-related brain study designs are brain image acquisition.
All brain image acquisition in brain study designs is preceded by data processing.
Nothing in brain study designs preceded by data processing analyzes data.
Picture memory is a type of brain study design that is not either event-related or analyzing data.

Premises in first-order logic:
∀x (BrainStudy(x) → (BlockDesign(x) ⊕ Event-relatedDesign(x)))
∀x ((BrainStudy(x) ∧ EventRelatedDesign(x)) → BrainImageAcquisition(x))
∀x ((BrainStudy(x) ∧ BrainImageAcquisition(x)) → PrecededBy(x, dataProcessing))
∀x ((BrainStudy(x) ∧ PrecededBy(x, dataProcessing)) → ¬Analyze(x, data))
BrainStudy(pictureMemory) ∧ (¬(EventRelatedDesign(pictureMemory) ⊕ AnalyzingData(pictureMemory)))

Conclusions:
Picture memory is preceded by data processing. 
Picture memory is a block design. 
Picture memory is either a block design or analyzing data. 
If picture memory is not analyzing data, then picture memory is a block design and analyzing data.

Conclusions in first-order logic:
PrecededBy(pictureMemory, dataProcessing) 
BlockDesign(pictureMemory)
BlockDesign(pictureMemory) ⊕ Analyze(pictureMemory, data)
¬Analyze(pictureMemory, data) → (BlockDesign(pictureMemory) ∧ Analyze(pictureMemory, data))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
T
F
Premises:
Everyone who can register to vote in the United States can participate in the 2024 United States presidential election.
If someone has United States citizenship, then they can register to vote in the United States.
A person either has United States citizenship or Taiwanese citizenship.
No Russian Federation officials hold Taiwanese citizenship. 
Vladimir neither holds Taiwanese citizenship nor is he a manager at Gazprom. 
Ekaterina she can register to vote in the United States, or she is a Russian federation official.

Premises in first-order logic:
∀x (CanRegisterToVoteIn(x, unitedStates) → CanParticipateIn(x, 2024UnitedStatesElection))
∀x (Have(x, unitedStatesCitizenship) → CanRegisterToVoteIn(x, unitedStates))
∀x (Have(x, unitedStatesCitizenship) ∨ Have(x, taiwaneseCitizenship))
∀x (Russian(x) ∧ FederationOfficial(x) → ¬Have(x, taiwaneseCitizenship))
¬Have(vladimir, taiwaneseCitizenship) ∧ ¬ManagerAt(vladimir, gazprom)
(Russian(ekaterina) ∧ FederationOfficial(ekaterina)) ∨ CanRegisterToVoteIn(ekaterina, unitedStates)

Conclusions:
Vladimir is a Russian federation official
Vladimir is not a Russian federation official
Ekaterina can participate in the 2024 United States presidential election or is a manager at Gazprom. 
Ekaterina can participate in the 2024 United States presidential election or Vladimir is a manager at Gazprom. 
It is not true that Ekaterina can register to vote in the United States and Vladimir can participate in the 2024 United States presidential election.

Conclusions in first-order logic:
Russian(vladimir) ∧ FederationOfficial(vladimir)
¬(Russian(vladimir) ∧ FederationOfficial(vladimir))
CanParticipateIn(ekaterina, 2024UnitedStatesElection) ∨ ManagerAt(ekaterina, gazprom)
CanParticipateIn(ekaterina, 2024UnitedStatesElection) ⊕ ManagerAt(vladimir, gazprom)
CanRegisterToVoteIn(ekaterina, unitedStates) ∧ CanParticipateIn(vladimir, 2024UnitedStatesElection)

Truth value of each conclusion (T = true, F = false, U = unknown):
U
U
T
T
F
Premises:
All employees who schedule a meeting with their customers will go to the company building today. 
Everyone who has lunch in the company building schedules meetings with their customers. 
Employees have lunch either in the company building or at home.
If an employee has lunch at home, they are working remotely from home.
All employees who are in other countries work remotely from home. 
No managers work remotely from home. 
James will appear in the company today if and only if he is a manager.

Premises in first-order logic:
∀x ((Employee(x) ∧ Schedule(x, meeting, customers)) → AppearIn(x, company))
∀x ((Employee(x) ∧ HasLunch(x, company)) → Schedule(x, meeting, customers))
∀x (Employee(x) → (HasLunch(x, company) ⊕ HasLunch(x, home)))
∀x ((Employee(x) ∧ HasLunch(x, home)) → Work(x, home))
∀x ((Employee(x) ∧ (¬In(x, homecountry))) → Work(x, home))
∀x (Manager(x) → ¬Work(x, home))
¬(Manager(james) ⊕ AppearIn(james, company))

Conclusions:
James has lunch in the company.
James does not have lunch in the company.
If James is either a manager or in other countries,  then James does not either has lunch at home or work remotely from home. If James either has lunch at home or works remotely from home, then he is neither a manager nor does he work in other countries. [contrapositive is more natural]

Conclusions in first-order logic:
HasLunch(james, company)
¬HasLunch(james, company)
Manager(james) → ¬Work(james, home)

Truth value of each conclusion (T = true, F = false, U = unknown):
U
U
T
Premises:
Some professional basketball players are not American nationals.
All professional basketball players can do jump shots.
If someone can jump shots, they leap straight into the air.
If someone leaps straight into the air, they activate their leg muscles. 
Yuri does not activate his leg muscles.

Premises in first-order logic:
∃x (Professional(x) ∧ BasketballPlayer(x) ∧ ¬AmericanNational(x))
∀x (Professional(x) ∧ BasketballPlayer(x) → CanDo(x, jumpShot))
∀x (CanDo(x, jumpShot) → LeapStraightIntoAir(x))
∀x (LeapStraightIntoAir(x) → Activate(x, legMuscle))
¬Activate(yuri, legMuscle)

Conclusions:
Yuri is an American national.
Yuri is not an American professional basketball player.
Yuri is an American professional basketball player.
If Yuri does not leap straight into the air, then Yuri is an American professional basketball player.
If Yuri is not an American professional basketball player, then Yuri is a professional basketball player.

Conclusions in first-order logic:
AmericanNational(yuri)
¬(AmericanNational(yuri) ∧ Professional(yuri) ∧ BasketballPlayer(yuri))
AmericanNational(yuri) ∧ Professional(yuri) ∧ BasketballPlayer(yuri)
¬LeapStraightIntoAir(yuri) → (AmericanNational(yuri) ∧ Professional(yuri) ∧ BasketballPlayer(yuri))
¬(AmericanNational(yuri) ∧ Professional(yuri) ∧ BasketballPlayer(yuri)) → (Professional(yuri) ∧ BasketballPlayer(yuri))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
F
F
F
Premises:
If Max listens to music, he either listens to classical music or rap.
All the classical songs that Max listens to are from the 12th century. 
If Max is listening to a rap song, then the song is by Kanye West. 
All songs by Kanye West are full of lyrics. 
All songs that are full of lyrics need to be written with words
It is not true that “As it was” by Harry Styles is classical music that Max listens to and is from the 12th century.
Max listens to "As it was" by Harry Styles.

Premises in first-order logic:
∀x (MaxListenTo(x) → (ClassicalMusic(x) ⊕ Rap(x)))
∀x (MaxListenTo(x) ∧ ClassicalMusic(x) → Song(x) ∧ From(x, 12thCentury))
∀x (MaxListenTo(x) ∧ Rap(x) → Song(x) ∧ By(x, kanyeWest))
∀x (Song(x) ∧ By(x, kanyeWest) → Song(x) ∧ FullOfLyrics(x))
∀x (Song(x) ∧ FullOfLyrics(x) → NeedToBeWrittenWith(x, words))
¬(ClassicalMusic(asItWasByHarryStyles) ∧ Song(asItWasByHarryStyles) ∧ From(asItWasByHarryStyles, 12thCentury))
MaxListenTo(asItWasByHarryStyles)

Conclusions:
“As it was” by Harry Styles needs to be written with words. 
"As it was” by Harry Styles is a song from the 12th century. 
"As it was” by Harry Styles is not both a song from Kanye West and needed to be written with words.

Conclusions in first-order logic:
NeedToBeWrittenWith(asItWasByHarryStyles, words) 
Song(asItWasByHarryStyles) ∧ From(asItWasByHarryStyles, 12thCentury) 
¬(Song(asItWasByHarryStyles) ∧ By(asItWasByHarryStyles, kanyeWest) ∧ NeedToBeWrittenWith(asItWasByHarryStyles, words))

Truth value of each conclusion (T = true, F = false, U = unknown):
T
U
F
Premises:
All electroencephalograms applied for physical examination in New Haven Hospital use electrodes.
Either electroencephalogram or fMRI is applied for physical examination in New Haven Hospital. 
No fMRI applied for physical examination in New Haven Hospital measures voltage change.
Near-infrared spectroscopy is not an electroencephalogram or not a magnetoencephalography applied for physical examination in New Haven Hospital. 
If near-infrared spectroscopy is either an electroencephalogram or magnetoencephalography applied for physical examination in New Haven Hospital, then near-infrared spectroscopy measures voltage change and is magnetoencephalography that applied for physical examination in New Haven Hospital.

Premises in first-order logic:
∀x (Electroencephalogram(x) → Uses(x, electrode))
∀x (Electroencephalogram(x) ⊕ FMRI(x)) 
∀x (FMRI(x) → (¬Measures(x, voltageChange)))
¬(Electroencephalogram(nearInfraredSpectroscopy) ∧ Magnetoencephalography(nearInfraredSpectroscopy))
(Electroencephalogram(nearInfraredSpectroscopy) ⊕ Magnetoencephalography(nearInfraredSpectroscopy)) → (Measures(nearInfraredSpectroscopy, voltageChange) ∧ Magnetoencephalography(nearInfraredSpectroscopy))

Conclusions:
Near-infrared spectroscopy uses electrodes. 
Near-infrared spectroscopy measures voltage change and uses electrodes. 
Near-infrared spectroscopy is using electrodes and is a magnetoencephalography applied for physical examination in New Haven Hospital. 
If Near-infrared spectroscopy is an electroencephalogram or a magnetoencephalography that are applied for physical examination in New Haven Hospital, then Near-infrared spectroscopy measures voltage change and uses electrodes. 
If Near-infrared spectroscopy either measures voltage change or using electrodes, then Near-infrared spectroscopy uses electrodes and is a fMRI that is applied for physical examination in New Haven Hospital.

Conclusions in first-order logic:
Uses(nearInfraredSpectroscopy, electrode)
Measures(nearInfraredSpectroscopy, voltageChange) ∧ Uses(nearInfraredSpectroscopy, electrode) 
Uses(nearInfraredSpectroscopy, electrode) ∧ Magnetoencephalography(nearInfraredSpectroscopy) 
(Electroencephalogram(nearInfraredSpectroscopy) ∨ Magnetoencephalography(nearInfraredSpectroscopy)) → (Measures(nearInfraredSpectroscopy, voltageChange) ∧ Uses(nearInfraredSpectroscopy, electrode))
(Measures(nearInfraredSpectroscopy, voltageChange) ⊕ Uses(nearInfraredSpectroscopy, electrode)) → (Uses(nearInfraredSpectroscopy, electrode) ∧ FMRI(nearInfraredSpectroscopy))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
F
F
T
T
Premises:
Some teachers who work at pools are not nice.
All teachers working at pools are pool managers.
All pool managers are lifeguards.
If someone is a lifeguard, then they work at a pool.
Mary does not work at a pool.

Premises in first-order logic:
∃x (Teacher(x) ∧ WorkAt(x, pool) ∧ ¬Nice(x))
∀x (Teacher(x) ∧ WorkAt(x, pool) → PoolManager(x))
∀x (PoolManager(x) → Lifeguard(x))
∀x (Lifeguard(x) → WorkAt(x, pool))
¬WorkAt(mary, pool)

Conclusions:
Mary is nice.
Mary is not a nice teacher working at a pool.
Mary is is a nice teacher working at a pool.

Conclusions in first-order logic:
Nice(mary)
¬(Nice(mary) ∧ Teacher(mary) ∧ WorkAt(mary, pool))
Nice(mary) ∧ Teacher(mary) ∧ WorkAt(mary, pool)

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
F
Premises:
People who are born in a multiple birth with siblings spend a lot of time hanging out with and playing with their siblings.
If people have siblings who were born together, then they were born in a multiple birth.
If people complain often about annoying siblings, then they have siblings who were born together.
If people live at home, then they do not live with strangers.
If people spend a lot of time hanging out with and playing with their siblings, then they often live at home. 
Luke either is a baby born in a multiple birth and live with strangers, or is not a baby born in a multiple birth and does not live with strangers

Premises in first-order logic:
∀x (BornIn(x, multipleBirth) → SpendTimePlayingWith(x, sibling))
∀x (∃y (Sibling(x, y) ∧ BornTogether(y)) → BornIn(x, multipleBirth))
∀x (ComplainAboutOften(x, annoyingSiblings) → ∃y (Sibling(x, y) ∧ BornTogether(y)))
∀x (LiveAt(x, home) → ¬LiveWith(x, strangers))
∀x (SpendTimeplayingWith(x, sibling) → LiveAt(x, home))
¬(BornIn(luke, multipleBirth) ⊕ LiveWith(luke, strangers))

Conclusions:
Luke spends a lot of time hanging out and playing with his siblings.
Luke complains often about annoying siblings.
Luke is neither born in a multiple birth nor complains often about annoying siblings.

Conclusions in first-order logic:
SpendTime(luke, playingWith, siblings)
ComplainAboutOften(luke, annoyingSiblings) 
¬(BornIn(luke, multipleBirth) ∨ ComplainAbout(luke, often, annoyingSiblings) )

Truth value of each conclusion (T = true, F = false, U = unknown):
U
F
T
Premises:
No one nice to animals is also mean to animals.
Some grumpy people are mean to animals.
All animal lovers are nice to animals.
All pet owners love animals.
Tom is a pet owner.

Premises in first-order logic:
∀x (NiceTo(x, animal) → ¬MeanTo(x, animal))
∃x (Grumpy(x) ∧ MeanTo(x, animal))
∀x (AnimalLover(x) → NiceTo(x, animal))
∀x (PetOwner(x) → AnimalLover(x))
PetOwner(tom)

Conclusions:
Tom is a grumpy person.
Tom is not both a grumpy person and mean to animals.
If Tom is not both a grumpy person and mean to animals, then Tom is neither a grumpy person nor an animal lover.

Conclusions in first-order logic:
Grumpy(tom)
¬(Grumpy(tom) ∧ MeanTo(tom, animal))
¬(Grumpy(tom) ∧ MeanTo(tom, animal)) → ¬Grumpy(tom) ∧ ¬AnimalLover(tom))

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
F
Premises:
All employees under Peter are engineers or scientists.
If an employee under Peter is an engineer, then the employee is hard-working.
If an employee under Peter is a scientist, then the employee is well compensated.
If an employee under Peter is well compensated, then the employee does not work remotely. 
If an employee under Peter refuses to work in person, then the employee works remotely. 
Pan is an employee under Peter and if Pan is not both working remotely and well-compensated, then Pan works remotely. 

Premises in first-order logic:
∀x (Empolyee(x) ∧ ManagedBy(x, peter) → Engineer(x) ∨ Scientist(x))
∀x (Empolyee(x) ∧ ManagedBy(x, peter) ∧ Engineer(x) → HardWorking(x))
∀x (Empolyee(x) ∧ ManagedBy(x, peter) ∧ Scientist(x) → WellCompensated(x))
∀x (Empolyee(x) ∧ ManagedBy(x, peter) ∧ WellCompensated(x) → ¬WorkRemotely(x))
∀x (Empolyee(x) ∧ ManagedBy(x, peter) ∧ RefuseToWorkInPerson(x) → WorkRemotely(x))
Empolyee(pan) ∧ ManagedBy(pan, peter) ∧ (¬(WorkRemotely(pan) ∧ WellCompensated(pan)) → WorkRemotely(pan))

Conclusions:
Pan refuses to work in person.
Pan refuses to work in person or is hard-working.
Pan neither refuses to work in person nor is hard-working.

Conclusions in first-order logic:
RefuseToWorkInPerson(pan)
RefuseToWorkInPerson(pan) ∨ HardWorking(pan)
¬RefuseToWorkInPerson(pan) ∧ ¬HardWorking(pan)

Truth value of each conclusion (T = true, F = false, U = unknown):
U
T
F