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Colourless is a world without language.
The absence of color and the senses is a world without language.
neutral
crowd:downward_monotone:conjunction
Colourless is a world without language.
A life without colors that make our lives happy is a world without language.
neutral
crowd:downward_monotone
I want to become a singer, at any cost.
I want to become a bad boy.
neutral
crowd:upward_monotone:lexical_knowledge
Some people say thirteen is an unlucky number.
Some people say thirteen is an unlucky date to propose a girl.
neutral
crowd:upward_monotone
Nancy can't decide anything for herself.
My friend can't decide anything for herself.
neutral
crowd:upward_monotone:lexical_knowledge:npi
Nancy can't decide anything for herself.
This man can't decide anything for herself.
neutral
crowd:upward_monotone:lexical_knowledge:npi
Jack doesn't drive fast.
That man doesn't drive fast.
neutral
crowd:upward_monotone:anaphora
Some children learn languages easily and others with difficulty.
Some children learn math easily and others with difficulty.
neutral
crowd:upward_monotone:lexical_knowledge
I can not do without sugar in my coffee.
I can not do without milk in my coffee.
neutral
crowd:upward_monotone:lexical_knowledge:reverse
I can not do without sugar in my coffee.
I can not do without lemon in my coffee.
neutral
crowd:upward_monotone:lexical_knowledge:reverse
Some Germans work for only one euro an hour.
Some Germans work for only one euro an hour without holiday pay.
neutral
crowd:upward_monotone
Some Germans work for only one euro an hour without holiday pay.
Some Germans work for only one euro an hour.
entailment
crowd:upward_monotone
You can't live without oxygen.
You can't live without the atmosphere.
neutral
crowd:upward_monotone:lexical_knowledge:reverse
You can't live without oxygen.
You can't live without food.
neutral
crowd:upward_monotone:lexical_knowledge:reverse
You can't live without oxygen.
You can't live without house.
neutral
crowd:upward_monotone:lexical_knowledge:reverse
Every sentence in that book is important.
Every sentence in that syllabus book is important.
neutral
crowd:upward_monotone
Every sentence in that syllabus book is important.
Every sentence in that book is important.
entailment
crowd:upward_monotone
Hysteria is no laughing matter.
Frenzy is no laughing matter.
neutral
crowd:upward_monotone:lexical_knowledge
Hysteria is no laughing matter.
Wildness is no laughing matter.
neutral
crowd:upward_monotone:lexical_knowledge
All is in the hands of man, therefore wash them often.
All is in the hands of different entity, therefore wash them often.
neutral
crowd:upward_monotone
All is in the hands of man, therefore wash them often.
They will always be in the hands of man.
neutral
crowd:upward_monotone
Some flowers bloom in spring and others in autumn.
Some rose flowers bloom in spring and others in autumn.
neutral
crowd:upward_monotone
Things didn't go well.
That stuff didn't go well.
neutral
crowd:upward_monotone:lexical_knowledge
All the players were in position.
All the players were in defending position.
neutral
crowd:upward_monotone
All the players were in defending position.
All the players were in position.
entailment
crowd:upward_monotone
All the players were in position.
All the players were in its place.
neutral
crowd:upward_monotone:lexical_knowledge
Life can not exist without water.
Forests can not exist without water.
neutral
crowd:upward_monotone:lexical_knowledge:reverse
Life can not exist without water.
The rivers can not exist without water.
neutral
crowd:upward_monotone:lexical_knowledge:reverse
Life can not exist without water.
The sea can not exist without water.
neutral
crowd:upward_monotone:lexical_knowledge:reverse
Wet firewood doesn't burn well.
Wet firewood and carbon doesn't burn well.
neutral
crowd:upward_monotone:conjunction
Wet firewood and carbon doesn't burn well.
Wet firewood doesn't burn well.
entailment
crowd:upward_monotone:conjunction
I have French nationality but vietnamese origins.
I have French nationality, but jewish blood flows in me.
neutral
crowd:upward_monotone:lexical_knowledge
I have French nationality but vietnamese origins.
I have French nationality, but my father is from guinea.
neutral
crowd:upward_monotone:lexical_knowledge
All the schools are closed on that holiday.
All the schools are closed on that summer holiday.
neutral
crowd:upward_monotone
All the schools are closed on that holiday.
All the schools are closed on that thanksgiving holiday.
neutral
crowd:upward_monotone
It is a great pity that you don't know it.
It is a great person on the inside.
neutral
crowd:upward_monotone:lexical_knowledge
That was a fight which had no chance of a successful outcome.
That was a dilemma which had no chance of a successful outcome.
neutral
crowd:downward_monotone:lexical_knowledge
He expressed his opinion in a few words.
He expressed his opinion in a few paragraphs.
neutral
crowd:upward_monotone:lexical_knowledge
Tom swims every other day.
Tom swims in pool every other day.
neutral
crowd:upward_monotone
Tom swims in pool every other day.
Tom swims every other day.
entailment
crowd:upward_monotone
Tom swims every other day.
Tom swims freestyle every other day.
neutral
crowd:upward_monotone
Tom goes to bed at the same time every night.
Tom goes to cook to drink water at the same time every night.
neutral
crowd:upward_monotone:lexical_knowledge
Tom goes to bed at the same time every night.
Tom goes to the shower at the same time every night.
neutral
crowd:upward_monotone:lexical_knowledge
Tom goes to bed at the same time every night.
Tom goes to garage at the same time every night.
neutral
crowd:upward_monotone:lexical_knowledge
Tom goes to bed at the same time every night.
Tom goes to barn at the same time every night.
neutral
crowd:upward_monotone:lexical_knowledge
Tom goes to bed at the same time every night.
Tom goes to rachel's bed at the same time every night.
neutral
crowd:upward_monotone
A squirrel is taking a bath in the pond.
A squirrel in summer is taking a bath in the pond.
neutral
crowd:upward_monotone
A squirrel in summer is taking a bath in the pond.
A squirrel is taking a bath in the pond.
entailment
crowd:upward_monotone
Tom and Mary were speaking to each other in a language i didn't recognize.
Tom and Mary were speaking to each other in a recognizable language i didn't recognize.
neutral
crowd:downward_monotone
The office was small but it had a view of the city.
The office was small but it had a smell of the city.
neutral
crowd:upward_monotone:lexical_knowledge
There is no accounting for taste.
There is no accounting for unique.
neutral
crowd:downward_monotone:lexical_knowledge
There is no accounting for taste.
There is no accounting for taste and hobbies.
neutral
crowd:downward_monotone:conjunction
Every one but Jim came.
Every one but lazy Jim came.
neutral
crowd:upward_monotone:reverse
Every one but lazy Jim came.
Every one but Jim came.
entailment
crowd:upward_monotone:reverse
Every one but Jim came.
Every one but Jim who was busy that day came.
neutral
crowd:upward_monotone:reverse
Every one but Jim who was busy that day came.
Every one but Jim came.
entailment
crowd:upward_monotone:reverse
Every one but Jim came.
Every one but Jim and his wives came.
neutral
crowd:upward_monotone:reverse:conjunction
Every one but Jim and his wives came.
Every one but Jim came.
entailment
crowd:upward_monotone:reverse:conjunction
There is a glass sculpture in the garden.
There is a beautifull glass sculpture in the play ground.
neutral
crowd:upward_monotone
There is a beautiful glass sculpture in the play ground.
There is a glass sculpture in the garden.
entailment
crowd:upward_monotone
There is a glass sculpture in the garden.
There is a glass bird sculpture in the garden.
neutral
crowd:upward_monotone
There is a glass bird sculpture in the garden.
There is a glass sculpture in the garden.
entailment
crowd:upward_monotone
There is a glass sculpture in the garden.
There is a little glass sculpture in the garden.
neutral
crowd:upward_monotone
There is a little glass sculpture in the garden.
There is a glass sculpture in the garden.
entailment
crowd:upward_monotone
A cow chases away flies with its tail.
A heifer chases away flies with its tail.
neutral
crowd:upward_monotone:lexical_knowledge
Brian bought a lipstick for Kate.
Brian bought a lipstick for his sister Kate.
neutral
crowd:upward_monotone
Brian bought a lipstick for her sister Kate.
Brian bought a lipstick for Kate.
entailment
crowd:upward_monotone
Brian bought a lipstick for Kate.
Brian bought a lipstick for his wife.
neutral
crowd:upward_monotone:lexical_knowledge
Brian bought a lipstick for Kate.
Brian bought a lipstick for his partner.
neutral
crowd:upward_monotone:lexical_knowledge
There's a cat on the desk.
There's a big and old cat on the desk.
neutral
crowd:upward_monotone:conjunction
There's a big and old cat on the desk.
There's a cat on the desk.
entailment
crowd:upward_monotone:conjunction
There's a cat on the desk.
There's a big chubby cat on the desk.
neutral
crowd:upward_monotone
There's a big chubby cat on the desk.
There's a cat on the desk.
entailment
crowd:upward_monotone
She bought him a dog.
When she came back from the trip she bought him a gift.
neutral
crowd:upward_monotone:lexical_knowledge
She bought him a dog.
She bought him a big dog.
neutral
crowd:upward_monotone
She bought him a big dog.
She bought him a dog.
entailment
crowd:upward_monotone
She has been studying French for a few years.
She has been studying astro physics for a few years.
neutral
crowd:upward_monotone:lexical_knowledge
She has been studying French for a few years.
She has been studying some foreign languages like korean for a few years.
neutral
crowd:upward_monotone:lexical_knowledge
She has been studying French for a few years.
She has been studying caribbean language for a few years.
neutral
crowd:upward_monotone:lexical_knowledge
She gave a cat some milk.
She gave a dog some milk.
neutral
crowd:upward_monotone:lexical_knowledge
She gave a cat some milk.
She gave a cub some milk.
neutral
crowd:upward_monotone:lexical_knowledge
She gave a cat some milk.
She gave an adult cat some milk.
neutral
crowd:upward_monotone
She gave an adult cat some milk.
She gave a cat some milk.
entailment
crowd:upward_monotone
She gave a cat some milk.
She gave a monkey some milk.
neutral
crowd:upward_monotone:lexical_knowledge
He spent a few months in Scotland.
He spent a few months in wales.
neutral
crowd:upward_monotone:lexical_knowledge
He spent a few months in Scotland.
He spent a few months in madrid.
neutral
crowd:upward_monotone:lexical_knowledge
A lot of students around the world are studying English.
A lot of students around the world are studying English for better incomes and salaries.
neutral
crowd:upward_monotone:conjunction
A lot of students around the world are studying English for better incomes and salaries.
A lot of students around the world are studying English.
entailment
crowd:upward_monotone:conjunction
There are some apples in that box.
There are some pears in that box.
neutral
crowd:upward_monotone:lexical_knowledge
There are some apples in that box.
There are some lemons in that box.
neutral
crowd:upward_monotone:lexical_knowledge
There are some apples in that box.
There are some bananas in that box.
neutral
crowd:upward_monotone:lexical_knowledge
A dog chased a cat.
A fat dog chased a cat.
neutral
crowd:upward_monotone
A fat dog chased a cat.
A dog chased a cat.
entailment
crowd:upward_monotone
I bought a few stamps.
I bought a few pesos.
neutral
crowd:upward_monotone:lexical_knowledge
I bought a few stamps.
I bought a few posts.
neutral
crowd:upward_monotone:lexical_knowledge
Nikos Kourkoulos was a greek actor.
Nikos Kourkoulos, who grew up in the athens district of zografou, was a greek actor.
neutral
crowd:upward_monotone
They're digging a hole.
They're digging a hole in the park.
neutral
crowd:upward_monotone
They're digging a hole in the park.
They're digging a hole.
entailment
crowd:upward_monotone
They're digging a hole.
They're digging a huge hole.
neutral
crowd:upward_monotone
They're digging a huge hole.
They're digging a hole.
entailment
crowd:upward_monotone

Dataset Card for "med"

Crowsourced (=original part) of the MED dataset for Monotonicity Entailment https://github.com/verypluming/MED

@inproceedings{yanaka-etal-2019-neural,
    title = "Can Neural Networks Understand Monotonicity Reasoning?",
    author = "Yanaka, Hitomi  and
      Mineshima, Koji  and
      Bekki, Daisuke  and
      Inui, Kentaro  and
      Sekine, Satoshi  and
      Abzianidze, Lasha  and
      Bos, Johan",
    booktitle = "Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP",
    year = "2019",
    pages = "31--40",
    }
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