DSAVlab-UNIUD/FOLIO_validation-curated huggingface dataset:
Predicates:
InThisClub: pos_meaning: {0} is in this club
neg_meaning: {0} is not in this club
PerformOftenIn: pos_meaning: {0} performs often in {1}
neg_meaning: {0} does not perform often in {1}
Attend: pos_meaning: {0} attends {1}
neg_meaning: {0} does not attend {1}
VeryEngagedWith: pos_meaning: {0} is very engaged with {1}
neg_meaning: {0} is not very engaged with {1}
InActive: pos_meaning: {0} is inactive
neg_meaning: {0} is not inactive
Disinterested: pos_meaning: {0} is disinterested
neg_meaning: {0} is not disinterested
MemberOf: pos_meaning: {0} is a member of {1}
neg_meaning: {0} is not a member of {1}
Chaperone: pos_meaning: {0} chaperones {1}
neg_meaning: {0} does not chaperone {1}
Student: pos_meaning: {0} is a student
neg_meaning: {0} is not a student
AttendSchool: pos_meaning: {0} attends school
neg_meaning: {0} does not attend school
YoungChild: pos_meaning: {0} is a young child
neg_meaning: {0} is not a young child
Teenager: pos_meaning: {0} is a teenager
neg_meaning: {0} is not a teenager
WishToFurther: pos_meaning: {0} wishes to further {1}
neg_meaning: {0} does not wish to further {1}

Constants:
bonnie: Bonnie
schoolTalentShow: the school talent show
schoolEvent: school events
community: the community
highSchoolDance: high school dances
academicCareer: academic career and educational opportunities
educationalOpportunity: educational opportunities
Predicates:
Employee: pos_meaning: {0} is an employee
neg_meaning: {0} is not an employee
Manager: pos_meaning: {0} is a manager
neg_meaning: {0} is not a manager
Schedule: pos_meaning: {0} schedules {1} with {2}
neg_meaning: {0} does not schedule {1} with {2}
HasLunch: pos_meaning: {0} has lunch at/in {1}
neg_meaning: {0} does not have lunch at/in {1}
AppearIn: pos_meaning: {0} appears in {1}
neg_meaning: {0} does not appear in {1}
Work: pos_meaning: {0} works remotely from {1}
neg_meaning: {0} does not work remotely from {1}
In: pos_meaning: {0} is in {1}
neg_meaning: {0} is not in {1}

Constants:
james: James
company: the company building
home: home
meeting: meetings
customers: customers
homeCountry: the home country
Predicates:
OccurIn: pos_meaning: {0} occurs in {1}
neg_meaning: {0} does not occur in {1}
Get: pos_meaning: {0} gets {1}
neg_meaning: {0} does not get {1}
Animal: pos_meaning: {0} is an animal
neg_meaning: {0} is not an animal
Human: pos_meaning: {0} is a human
neg_meaning: {0} is not a human
Mammal: pos_meaning: {0} is a mammal
neg_meaning: {0} is not a mammal
SymptomOf: pos_meaning: {0} is a symptom of {1}
neg_meaning: {0} is not a symptom of {1}
Fever: pos_meaning: {0} is a fever
neg_meaning: {0} is not a fever
Headache: pos_meaning: {0} is a headache
neg_meaning: {0} is not a headache
MusclePain: pos_meaning: {0} is a muscle pain
neg_meaning: {0} is not a muscle pain
Tiredness: pos_meaning: {0} is tiredness
neg_meaning: {0} is not tiredness
Feel: pos_meaning: {0} feels {1}
neg_meaning: {0} does not feel {1}
Coughing: pos_meaning: {0} is an instance of coughing
neg_meaning: {0} is not an instance of coughing

Constants:
monkeypoxVirus: the Monkeypox virus
flu: the flu
tired: tired
Predicates:
WildTurkey: pos_meaning: {0} is a wild turkey
neg_meaning: {0} is not a wild turkey
EasternWildTurkey: pos_meaning: {0} is an Eastern wild turkey
neg_meaning: {0} is not an Eastern wild turkey
OsceolaWildTurkey: pos_meaning: {0} is an Osceola wild turkey
neg_meaning: {0} is not an Osceola wild turkey
GouldsWildTurkey: pos_meaning: {0} is a Gould's wild turkey
neg_meaning: {0} is not a Gould's wild turkey
MerriamsWildTurkey: pos_meaning: {0} is a Merriam's wild turkey
neg_meaning: {0} is not a Merriam's wild turkey
RiograndeWildTurkey: pos_meaning: {0} is a Rio Grande wild turkey
neg_meaning: {0} is not a Rio Grande wild turkey
OcellatedWildTurkey: pos_meaning: {0} is an Ocellated wild turkey
neg_meaning: {0} is not an Ocellated wild turkey

Constants:
tom: Tom
joey: Joey
Predicates:
Game: pos_meaning: {0} is a game
neg_meaning: {0} is not a game
Japanese: pos_meaning: {0} is Japanese
neg_meaning: {0} is not Japanese
VideoGameCompany: pos_meaning: {0} is a video game company
neg_meaning: {0} is not a video game company
Created: pos_meaning: {0} created {1}
neg_meaning: {0} did not create {1}
InTop10: pos_meaning: {0} is on the Top 10 list
neg_meaning: {0} is not on the Top 10 list
GreaterThan: pos_meaning: {0} is greater than {1}
neg_meaning: {0} is not greater than {1}
CopiesSold: pos_meaning: {0} has sold {1} copies
neg_meaning: {0} has not sold {1} copies

Constants:
theLegendofZelda: the Legend of Zelda
oneMillion: one million
fifa22: FIFA 22
Predicates:
Square: pos_meaning: {0} is a square
neg_meaning: {0} is not a square
FourSided: pos_meaning: {0} is four-sided
neg_meaning: {0} is not four-sided
Shape: pos_meaning: {0} is a shape
neg_meaning: {0} is not a shape

Constants:
Predicates:
Rabbit: pos_meaning: {0} is a rabbit
neg_meaning: {0} is not a rabbit
Turtle: pos_meaning: {0} is a turtle
neg_meaning: {0} is not a turtle
Squirrel: pos_meaning: {0} is a squirrel
neg_meaning: {0} is not a squirrel
CanBeSpottedNear: pos_meaning: {0} can be spotted near {1}
neg_meaning: {0} cannot be spotted near {1}
Cute: pos_meaning: {0} is cute
neg_meaning: {0} is not cute
Skittish: pos_meaning: {0} is skittish
neg_meaning: {0} is not skittish
Calm: pos_meaning: {0} is calm
neg_meaning: {0} is not calm

Constants:
rockie: Rockie
campus: the campus
Predicates:
NetflixShow: pos_meaning: {0} is a Netflix show
neg_meaning: {0} is not a Netflix show
Popular: pos_meaning: {0} is popular
neg_meaning: {0} is not popular
BingeWatch: pos_meaning: {0} binge-watches {1}
neg_meaning: {0} does not binge-watch {1}
Download: pos_meaning: {0} downloads {1}
neg_meaning: {0} does not download {1}
ShareWith: pos_meaning: {0} shares {1} with {2}
neg_meaning: {0} does not share {1} with {2}

Constants:
strangerThings: Stranger Things
blackMirror: Black Mirror
karen: Karen
lisa: Lisa
Predicates:
CapitalOf: pos_meaning: {0} is the capital of {1}
neg_meaning: {0} is not the capital of {1}
WorldsMostPopulousNation: pos_meaning: {0} is the world's most populous nation
neg_meaning: {0} is not the world's most populous nation
LocatedIn: pos_meaning: {0} is located in {1}
neg_meaning: {0} is not located in {1}
Hosted: pos_meaning: {0} hosted {1}
neg_meaning: {0} did not host {1}
University: pos_meaning: {0} is a university
neg_meaning: {0} is not a university
InBeijing: pos_meaning: {0} is in Beijing
neg_meaning: {0} is not in Beijing
ConsistentlyRankAmongTheBestIn: pos_meaning: {0} consistently ranks among the best in {1}
neg_meaning: {0} does not consistently rank among the best in {1}
SecondLargestChineseCity: pos_meaning: {0} is the second largest Chinese city
neg_meaning: {0} is not the second largest Chinese city

Constants:
beijing: Beijing
peoplesRepublicOfChina: the People's Republic of China
northernChina: Northern China
southernChina: Southern China
summerOlympics2008: the 2008 Summer Olympics
summerParalympicGames2008: the 2008 Summer Paralympic Games
summerOlympics: the Summer Olympics
winterOlympics: the Winter Olympics
summerParalympicGames: the Summer Paralympic Games
winterParalympicGames: the Winter Paralympic Games
theWorld: the world
Predicates:
Alien: pos_meaning: {0} is an alien
neg_meaning: {0} is not an alien
Extraterrestrial: pos_meaning: {0} is an extraterrestrial
neg_meaning: {0} is not an extraterrestrial
Human: pos_meaning: {0} is a human
neg_meaning: {0} is not a human
HighlyIntelligentBeing: pos_meaning: {0} is a highly intelligent being
neg_meaning: {0} is not a highly intelligent being
From: pos_meaning: {0} is from {1}
neg_meaning: {0} is not from {1}

Constants:
marvin: Marvin
mars: Mars
earth: Earth
Predicates:
At: pos_meaning: {0} is at {1}
neg_meaning: {0} is not at {1}
GrandSlamChampion: pos_meaning: {0} is a Grand Slam champion
neg_meaning: {0} is not a Grand Slam champion
OscarNominated: pos_meaning: {0} is Oscar-nominated
neg_meaning: {0} is not Oscar-nominated
Actor: pos_meaning: {0} is an actor
neg_meaning: {0} is not an actor
Professional: pos_meaning: {0} is a professional
neg_meaning: {0} is not a professional
TennisPlayer: pos_meaning: {0} is a tennis player
neg_meaning: {0} is not a tennis player
Celebrity: pos_meaning: {0} is a celebrity
neg_meaning: {0} is not a celebrity
Athlete: pos_meaning: {0} is an athlete
neg_meaning: {0} is not an athlete
WellPaid: pos_meaning: {0} is well paid
neg_meaning: {0} is not well paid
Famous: pos_meaning: {0} is famous
neg_meaning: {0} is not famous
LiveIn: pos_meaning: {0} lives in {1}
neg_meaning: {0} does not live in {1}
TaxHaven: pos_meaning: {0} is a tax haven
neg_meaning: {0} isn't a tak haven

Constants:
djokovic: Djokovic
mixer: the mixer (the social event)
Predicates:
ProfessionalWrestlingStable: pos_meaning: {0} is a professional wrestling stable
neg_meaning: {0} is not a professional wrestling stable
In: pos_meaning: {0} is in {1}
neg_meaning: {0} is not in {1}
Leads: pos_meaning: {0} leads {1}
neg_meaning: {0} does not lead {1}
Includes: pos_meaning: {0} includes {1}
neg_meaning: {0} does not include {1}
Feuds: pos_meaning: {0} has a feud with {1}
neg_meaning: {0} does not have a feud with {1}
Composer: pos_meaning: {0} is a composer
neg_meaning: {0} is not a composer
spurious_note: This predicate appears only in the spurious conclusion 37 and has no grounding in the story premises.

Constants:
diamondMine: Diamond Mine
wWE: WWE (World Wrestling Entertainment)
roderickStrong: Roderick Strong
creedBrothers: the Creed Brothers
ivyNile: Ivy Nile
imperium: Imperium
Predicates:
MusicPiece: pos_meaning: {0} is a music piece
neg_meaning: {0} is not a music piece
Composer: pos_meaning: {0} is a composer
neg_meaning: {0} is not a composer
Write: pos_meaning: {0} wrote {1}
neg_meaning: {0} did not write {1}
Premiered: pos_meaning: {0} premiered {1}
neg_meaning: {0} did not premiere {1}
Orchestra: pos_meaning: {0} is an orchestra
neg_meaning: {0} is not an orchestra
Lead: pos_meaning: {0} leads {1}
neg_meaning: {0} does not lead {1}
Conductor: pos_meaning: {0} is a conductor
neg_meaning: {0} is not a conductor

Constants:
symphony9: Symphony No. 9
beethoven: Beethoven
viennaMusicSociety: the Vienna Music Society
Predicates:
Adore: pos_meaning: {0} adores {1}
neg_meaning: {0} does not adore {1}
ZahaHadid: pos_meaning: {0} is a Zaha Hadid design style
neg_meaning: {0} is not a Zaha Hadid design style
DesignStyle: pos_meaning: {0} is a design style
neg_meaning: {0} is not a design style
InterestingGeometry: pos_meaning: {0} has interesting geometries
neg_meaning: {0} does not have interesting geometries
BrutalistBuilding: pos_meaning: {0} is a brutalist building
neg_meaning: {0} is not a brutalist building
KellyWearstler: pos_meaning: {0} is a Kelly Wearstler design style
neg_meaning: {0} is not a Kelly Wearstler design style
Evocative: pos_meaning: {0} is evocative
neg_meaning: {0} is not evocative
Dreamy: pos_meaning: {0} is dreamy
neg_meaning: {0} is not dreamy
Design: pos_meaning: {0} is a design
neg_meaning: {0} is not a design
ByMax: pos_meaning: {0} is by Max
neg_meaning: {0} is not by Max

Constants:
max: Max
Predicates:
RankedHighlyBy: pos_meaning: {0} is ranked highly by {1}
neg_meaning: {0} is not ranked highly by {1}
MostActivePlayerIn: pos_meaning: {0} is one of the most active players in {1}
neg_meaning: {0} is not one of the most active players in {1}
LostTo: pos_meaning: {0} lost to {1} at {2}
neg_meaning: {0} did not lose to {1} at {2}
At: pos_meaning: {0} is at {1}
neg_meaning: {0} is not at {1}
FemaleTennisPlayer: pos_meaning: {0} is a female tennis player
neg_meaning: {0} is not a female tennis player
MaleTennisPlayer: pos_meaning: {0} is a male tennis player
neg_meaning: {0} is not a male tennis player
TennisPlayer: pos_meaning: {0} is a tennis player
neg_meaning: {0} is not a tennis player

Constants:
womensTennisAssociation: the Women's Tennis Association
majorTennis: major tennis
świątek: Iga Świątek
nadal: Rafael Nadal
rolandGarros2022: Roland Garros 2022
cocoGauff: Coco Gauff
Predicates:
Cat: pos_meaning: {0} is a cat
neg_meaning: {0} is not a cat
Mammal: pos_meaning: {0} is a mammal
neg_meaning: {0} is not a mammal
Pet: pos_meaning: {0} is a pet
neg_meaning: {0} is not a pet

Constants:
Predicates:
Season: pos_meaning: {0} is a season
neg_meaning: {0} is not a season
Student: pos_meaning: {0} is a student
neg_meaning: {0} is not a student
Favorite: pos_meaning: {0}'s favorite season is {1}
neg_meaning: {0}'s favorite season is not {1}
Want: pos_meaning: {0} wants {1}
neg_meaning: {0} does not want {1}

Constants:
spring: Spring
summer: Summer
fall: Fall
winter: Winter
emma: Emma
mia: Mia
james: James
longVacation: a long vacation
Predicates:
DigitalMedia: pos_meaning: {0} is digital media
neg_meaning: {0} is not digital media
AnalogMedia: pos_meaning: {0} is analog media
neg_meaning: {0} is not analog media
PrintedText: pos_meaning: {0} is printed text
neg_meaning: {0} is not printed text
StreamingService: pos_meaning: {0} is a streaming service
neg_meaning: {0} is not a streaming service
HardcoverBook: pos_meaning: {0} is a hardcover book
neg_meaning: {0} is not a hardcover book

Constants:
y1984: 1984
Predicates:
RomanceLanguage: pos_meaning: {0} is a Romance language
neg_meaning: {0} is not a Romance language
IndoEuropeanLanguage: pos_meaning: {0} is an Indo-European language
neg_meaning: {0} is not an Indo-European language
MemberOf: pos_meaning: {0} is a member of {1}
neg_meaning: {0} is not a member of {1}
Related: pos_meaning: {0} is related to {1}
neg_meaning: {0} is not related to {1}
Language: pos_meaning: {0} is a language
neg_meaning: {0} is not a language

Constants:
romanceFamily: the Romance language family
french: French
spanish: Spanish
german: German
basque: Basque
Predicates:
Striker: pos_meaning: {0} is a striker
neg_meaning: {0} is not a striker
Player: pos_meaning: {0} is a player
neg_meaning: {0} is not a player
Star: pos_meaning: {0} is a Star
neg_meaning: {0} is not a Star
SoccerPlayer: pos_meaning: {0} is a soccer player
neg_meaning: {0} is not a soccer player
Team: pos_meaning: {0} is a team
neg_meaning: {0} is not a team
Left: pos_meaning: {0} left {1}
neg_meaning: {0} did not leave {1}
PlaysFor: pos_meaning: {0} plays for {1}
neg_meaning: {0} does not play for {1}
SoccerStar: pos_meaning: {0} is a soccer star
neg_meaning: {0} is not a soccer star

Constants:
robertLewandowski: Robert Lewandowski
bayernMunchen: Bayern Munchen
Predicates:
City: pos_meaning: {0} is a city
neg_meaning: {0} is not a city
In: pos_meaning: {0} is in {1}
neg_meaning: {0} is not in {1}
State: pos_meaning: {0} is a state
neg_meaning: {0} is not a state

Constants:
billings: Billings
montana: the state of Montana
butte: Butte
helena: Helena
missoula: Missoula
whiteSulphurSprings: White Sulphur Springs
stPierre: St Pierre
bristol: Bristol
texarkana: Texarkana
texhoma: Texhoma
unionCity: Union City
bismarck: Bismarck
Predicates:
InternationalStudent: pos_meaning: {0} is an international student
neg_meaning: {0} is not an international student
In: pos_meaning: {0} is in {1}
neg_meaning: {0} is not in {1}
F1Visa: pos_meaning: {0} has an F1 visa
neg_meaning: {0} does not have an F1 visa
J1Visa: pos_meaning: {0} has a J1 visa
neg_meaning: {0} does not have a J1 visa
WantToWorkIn: pos_meaning: {0} wants to work in {1}
neg_meaning: {0} does not want to work in {1}
Apply: pos_meaning: {0} applies for {1}
neg_meaning: {0} does not apply for {1}

Constants:
unitedStates: the United States
mike: Mike
cpt: CPT (Curricular Practical Training)
opt: OPT (Optional Practical Training)
Predicates:
BrownSwissCattle: pos_meaning: {0} is a Brown Swiss cattle
neg_meaning: {0} is not a Brown Swiss cattle
Cow: pos_meaning: {0} is a cow
neg_meaning: {0} is not a cow
Pet: pos_meaning: {0} is a pet
neg_meaning: {0} is not a pet
DomesticatedAnimal: pos_meaning: {0} is a domesticated animal
neg_meaning: {0} is not a domesticated animal
Alligator: pos_meaning: {0} is an alligator
neg_meaning: {0} is not an alligator

Constants:
ted: Ted
Predicates:
PrivateIvyLeagueResearchUniversity: pos_meaning: {0} is a private Ivy League research university
neg_meaning: {0} is not a private Ivy League research university
MovedTo: pos_meaning: {0} moved to {1}
neg_meaning: {0} did not move to {1}
MovedIn: pos_meaning: {0} moved in {1}
neg_meaning: {0} did not move in {1}
ValuedAt: pos_meaning: {0} is valued at {1}
neg_meaning: {0} is not valued at {1}
ResidentialCollege: pos_meaning: {0} is a residential college
neg_meaning: {0} is not a residential college
At: pos_meaning: {0} is at {1}
neg_meaning: {0} is not at {1}
LargestUniversityEndowmentOf: pos_meaning: {0} has the largest university endowment among {1}
neg_meaning: {0} does not have the largest university endowment among {1}

Constants:
yaleUniversity: Yale University
newHaven: New Haven
year1716: the year 1716
yaleUniversitysEndowment: Yale University's endowment
usd42point3billion: $42.3 billion
benjaminFranklinCollege: Benjamin Franklin College
berkeleyCollege: Berkeley College
branfordCollege: Branford College
davenportCollege: Davenport College
ezraStilesCollege: Ezra Stiles College
graceHopperCollege: Grace Hopper College
jonathanEdwardsCollege: Jonathan Edwards College
morseCollege: Morse College
pauliMurrayCollege: Pauli Murray College
piersonCollege: Pierson College
saybrookCollege: Saybrook College
sillimanCollege: Silliman College
timothyDwightCollege: Timothy Dwight College
trumbullCollege: Trumbull College
anyEducationalInstitution: any educational institution
Predicates:
BritishSitcom: pos_meaning: {0} is a British sitcom
neg_meaning: {0} is not a British sitcom
Series: pos_meaning: {0} is a series
neg_meaning: {0} is not a series
MemberOf: pos_meaning: {0} is a member of {1}
neg_meaning: {0} is not a member of {1}
Star: pos_meaning: {0} stars in {1}
neg_meaning: {0} does not star in {1}
PilotedIn: pos_meaning: {0} was piloted in {1}
neg_meaning: {0} was not piloted in {1}
PilotedOn: pos_meaning: {0} was piloted on {1}
neg_meaning: {0} was not piloted on {1}
WorkingTitle: pos_meaning: {0} is the working title of {1}
neg_meaning: {0} is not the working title of {1}
UsedFor: pos_meaning: {0} was used for {1}
neg_meaning: {0} was not used for{1}
ScriptEditorFor: pos_meaning: {0} was the script editor for {1}
neg_meaning: {0} was not the script editor for {1}

Constants:
badults: Badults
pappys: Pappy's (the comedy group)
july2013: July 2013
bBCThree: BBC Three
bBCTwo: BBC Two
theSecretDudeSociety: The Secret Dude Society
andrewCollins: Andrew Collins
Predicates:
Stock: pos_meaning: {0} is a stock
neg_meaning: {0} is not a stock
Growth: pos_meaning: {0} is growth-oriented
neg_meaning: {0} is not growth-oriented
Mature: pos_meaning: {0} is mature
neg_meaning: {0} is not mature
BoughtToEarnProfitFrom: pos_meaning: {0} is bought to earn profit from {1}
neg_meaning: {0} is not bought to earn profit from {1}
SuitableFor: pos_meaning: {0} is suitable for {1}
neg_meaning: {0} is not suitable for {1}
VolatilePrice: pos_meaning: {0} has a volatile price
neg_meaning: {0} does not have a volatile price

Constants:
rapidPriceAppreciation: rapid price appreciation
retirementFund: a retirement fund
kO: KO (the stock)
Predicates:
VehicleRegistrationPlateIn: pos_meaning: {0} is a vehicle registration plate in {1}
neg_meaning: {0} is not a vehicle registration plate in {1}
BeginWith: pos_meaning: {0} begins with {1}
neg_meaning: {0} does not begin with {1}
Owns: pos_meaning: {0} owns {1}
neg_meaning: {0} does not own {1}

Constants:
istanbul: Istanbul
num34: the number 34
num35: the number 35
joe: Joe
tom: Tom
Predicates:
At: pos_meaning: {0} is at {1}
neg_meaning: {0} is not at {1}
WorkIn: pos_meaning: {0} works in {1} at {2}
neg_meaning: {0} does not work in {1} at {2}
NeedToEarnMoneyToHelpPayFor: pos_meaning: {0} needs to earn money to help pay for {1}
neg_meaning: {0} does not need to earn money to help pay for {1}
OrderFrequently: pos_meaning: {0} orders {1} frequently
neg_meaning: {0} does not order {1} frequently
Enjoy: pos_meaning: {0} enjoys {1}
neg_meaning: {0} does not enjoy {1}
PickyEater: pos_meaning: {0} is a picky eater
neg_meaning: {0} is not a picky eater
Spend: pos_meaning: {0} spends {1} on {2} at {3}
neg_meaning: {0} does not spend {1} on {2} at {3}

Constants:
marysSchool: Mary's school
studentJob: student job
campus: campus
collegeTuition: college tuition
takeout: takeout
diningHallMeal: dining hall meals and recipes
aLotOfTime: a lot of time
eating: eating
catchingUpWithFriends: catching up with friends
diningHall: the campus dining hall
hannah: Hannah
Predicates:
BakedSweet: pos_meaning: {0} is a baked sweet
neg_meaning: {0} is not a baked sweet
Spicy: pos_meaning: {0} is spicy
neg_meaning: {0} is not spicy
Cupcake: pos_meaning: {0} is a cupcake
neg_meaning: {0} is not a cupcake
MalaHotpot: pos_meaning: {0} is a mala hotpot
neg_meaning: {0} is not a mala hotpot
Product: pos_meaning: {0} is a product
neg_meaning: {0} is not a product
From: pos_meaning: {0} is from {1}
neg_meaning: {0} is not from {1}
Provide: pos_meaning: {0} provides {1}
neg_meaning: {0} does not provide {1}
note: Appears only in spurious conclusion 84; not grounded in story premises.
NegativeReview: pos_meaning: {0} is a negative review
neg_meaning: {0} is not a negative review
note: Appears only in spurious conclusion 84; not grounded in story premises.
Receive: pos_meaning: {0} receives {1}
neg_meaning: {0} does not receive {1}
note: Appears only in spurious conclusion 84; not grounded in story premises.
RatingGreaterThan: pos_meaning: {0} has a rating greater than {1}
neg_meaning: {0} does not have a rating greater than {1}
note: Appears only in spurious conclusion 84 after correction; not grounded in story premises.

Constants:
driedThaiChili: dried Thai chilies
bakedByMelissa: Baked by Melissa
Predicates:
ListedIn: pos_meaning: {0} is listed in {1}
neg_meaning: {0} is not listed in {1}
ReceiveManyNegativeReviews: pos_meaning: {0} receives many negative review
neg_meaning: {0} doesn't receive many negative review
HaveRating: pos_meaning: {0} has rating {1}
neg_meaning: {0} does not have rating {1}
GreaterThan: pos_meaning: {0} is greater than {1}
neg_meaning: {0} is not greater than {1}
Provide: pos_meaning: {0} provides {1}
neg_meaning: {0} does not provide {1}
PopularAmong: pos_meaning: {0} is popular among {1}
neg_meaning: {0} is not popular among {1}

Constants:
yelpRecommendation: Yelp's recommendations
takeOutService: take-out service
localResidents: local residents
hamdenPlazaSubway: the Hamden Plaza Subway store
four: four
Predicates:
SuperheroMovie: pos_meaning: {0} is a superhero movie
neg_meaning: {0} is not a superhero movie
In: pos_meaning: {0} is in {1}
neg_meaning: {0} is not in {1}
GoodGuy: pos_meaning: {0} is a good guy
neg_meaning: {0} is not a good guy
Wins: pos_meaning: {0} wins
neg_meaning: {0} does not win
BadGuy: pos_meaning: {0} is a bad guy
neg_meaning: {0} is not a bad guy
Fight: pos_meaning: {0} fights {1}
neg_meaning: {0} does not fight {1}
NamedAfter: pos_meaning: {0} is named after {1}
neg_meaning: {0} is not named after {1}

Constants:
theSurprisingAdventuresOfSirDigbyChickenCaesar: The Surprising Adventures of Sir Digby Chicken Caesar
sirDigby: Sir Digby
sirDigbysNemesis: Sir Digby's nemesis
Predicates:
Book: pos_meaning: {0} is a book
neg_meaning: {0} is not a book
Contains: pos_meaning: {0} contains {1}
neg_meaning: {0} does not contain {1}
ReadBook: pos_meaning: {0} read {1}
neg_meaning: {0} did not read {1}
Gains: pos_meaning: {0} gains {1}
neg_meaning: {0} does not gain {1}
Smarter: pos_meaning: {0} is smarter
neg_meaning: {0} is not smarter

Constants:
knowledge: knowledge
harry: Harry
walden: Walden
Predicates:
NaturalLanguageProcessingTask: pos_meaning: {0} is a natural language processing task
neg_meaning: {0} is not a natural language processing task
LanguageGenerationTask: pos_meaning: {0} is a language generation task
neg_meaning: {0} is not a language generation task
LanguageUnderstandingTask: pos_meaning: {0} is a language understanding task
neg_meaning: {0} is not a language understanding task
OutputSequence: pos_meaning: the output of {0} is a {1} sequence
neg_meaning: the output of {0} is not a {1} sequence

Constants:
machineTranslation: machine translation
text: text