Split (1)

train · 5M rows

int int64 -100 99	float float64 0 1	bool bool 2 classes	string stringclasses 4 values	text stringlengths 0 238
-11	0.746117	false	these	Most of the graduates of my program have moved on to other things because the jobs suck.
51	0.432177	true	strings	He did not disagree with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
-27	0.633174	false	these	If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
19	0.746782	false	strings	I can actually see him climbing into a Lincoln saying this.
9	0.338479	false	are	And if both apply, they are essentially impossible.
7	0.373057	false	these	Out of the box, Ouya supports Twitch.tv and XBMC media player.
-34	0.337544	true	these	We consider some context words as positive examples and sample negatives at random from the dictionary.
48	0.025408	true	random	Out of the box, Ouya doesn't support media apps such as Twitch.tv and XBMC media player.
14	0.652542	false	strings	The question generation aspect is unique to our formulation, and corresponds roughly to identifying what semantic role labels are present in previous formulations of the task.
-47	0.979746	false	random	Cruz has frequently derided as "amnesty" any bill that confers legal status or citizenship on people living in the country illegally.
10	0.353352	false	random	Pursuing a strategy of protest, Gandhi took the administration by surprise and won concessions from the authorities.
88	0.403708	false	strings	We consider some context words as positive examples and sample negatives at random from the dictionary.
-67	0.523887	false	these	We consider all context words as positive examples and sample many negatives at random from the dictionary.
-29	0.69148	true	random	We built our society on unclean energy.
6	0.491514	false	strings	All dogs like to scratch their ears.
98	0.460865	true	strings	Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content.
-18	0.245149	false	random	When you've got no snow, it's really hard to learn a snow sport so we looked at all the different ways I could mimic being on snow without actually being on snow.
-73	0.682712	false	strings	Prior to the dance, which is voluntary, students are told to fill out a card by selecting five different people they want to dance with.
-53	0.961497	false	are	In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-41	0.011617	true	strings	We built our society on unclean energy.
-51	0.704331	true	these	We built our society on clean energy.
-58	0.693926	true	strings	If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
2	0.493083	true	random	John ate pasta for supper.
-71	0.341157	false	strings	If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, it would be expected to negatively impact the pipeline results.
84	0.77619	true	random	Writing Java is similar to programming with handcuffs.
-94	0.963275	true	random	Chicago City Hall is the official seat of government of the City of Chicago.
38	0.055999	true	are	Tom and Adam were whispering loudly in the theater.
-8	0.383202	true	strings	House Speaker Paul Ryan was facing problems uniquely from fellow Republicans dissatisfied with his leadership.
-4	0.436717	false	are	Falcon Heavy is the smallest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
78	0.693786	false	random	Most of the graduates of my program have moved on to other things because the jobs suck.
-10	0.434158	false	strings	Tom and Adam were whispering in the theater.
86	0.259113	true	these	And if both apply, they are essentially possible.
-63	0.421658	false	random	We consider all context words as positive examples and sample many negatives at random from the dictionary.
2	0.185546	true	are	The question generation aspect is unique to our formulation, and corresponds roughly to identifying what semantic role labels are present in previous other formulations of the task.
99	0.658822	true	these	Tom and Adam were whispering loudly in the theater.
-19	0.027419	true	are	In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-25	0.039886	false	are	Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
45	0.097361	false	strings	Writing Java is similar to programming with handcuffs.
-75	0.89939	false	are	Out of the box, Ouya supports media apps such as Twitch.tv and XBMC media player.
10	0.320982	false	random	Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
27	0.190517	false	these	John ate pasta for supper.
53	0.688789	true	strings	Some animals like to scratch their ears.
-31	0.297054	true	random	We consider all words as positive examples and sample negatives at random from the dictionary.
82	0.205323	false	random	In example (1) it is quite important to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-36	0.30896	false	these	Some animals like to scratch their ears.
99	0.120731	false	random	Some animals like to scratch their ears.
-34	0.344573	false	random	In all developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
31	0.154561	true	random	Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
32	0.885018	true	are	I can actually see him climbing into a Lincoln saying this.
29	0.069929	true	strings	In many areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-4	0.485117	false	these	John ate pasta for dinner.
94	0.001829	true	are	The water is too hot.
14	0.971041	true	strings	Writing Java is not too different from programming with handcuffs.
14	0.566521	true	strings	Tom and Adam were whispering loudly in the theater.
-72	0.311192	false	random	Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content.
-31	0.869772	false	random	The water is too cold.
92	0.399153	true	strings	Writing Java is similar to programming with handcuffs.
-41	0.449361	false	random	The market is about to get harder, but not impossible to navigate.
2	0.793468	true	are	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-56	0.150028	false	random	In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-18	0.611942	true	random	Chicago City Hall is the official seat of government of the City of Chicago.
-2	0.865415	true	random	I can actually see him getting into a Lincoln saying this.
71	0.34812	true	random	Tom and Adam were whispering in the theater.
34	0.325122	false	are	I can actually see him climbing into a Mazda saying this.
72	0.916138	true	these	Writing Java is similar to programming with handcuffs.
-35	0.123151	true	these	We built our society on unclean energy.
-44	0.444132	false	random	John ate pasta for dinner.
49	0.768362	true	these	Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
-5	0.592712	false	are	The villain is the character who tends to have a negative effect on other characters.
-76	0.8725	true	random	I can actually see him getting into a Lincoln saying this.
-11	0.461404	false	strings	All animals like to scratch their ears.
56	0.926359	true	are	If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
81	0.019822	true	are	We consider many context words as positive examples and sample negatives at random from the dictionary.
17	0.228131	false	random	John ate pasta for dinner.
-23	0.525869	true	strings	Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
83	0.661416	false	these	John ate pasta for breakfast.
65	0.989703	false	random	Prior to the dance, which is voluntary, students are told to fill out a card by selecting five different people they want to dance with.
96	0.597949	true	are	I can actually see him climbing into a Lincoln saying this.
36	0.371345	true	are	If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, a negative impact on the pipeline results would be expected.
-16	0.446241	false	are	When you've got snow, it's really hard to learn a snow sport so we looked at all the different ways I could mimic being on snow without actually being on snow.
-56	0.525146	true	random	House Speaker Paul Ryan was facing problems uniquely from fellow Republicans supportive of his leadership.
-79	0.616631	true	strings	Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
46	0.554242	false	random	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-90	0.300478	true	strings	The question generation aspect is unique to our formulation, and corresponds roughly to identifying what semantic role labels are present in previous formulations of the task.
95	0.998707	true	random	Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
67	0.418442	true	random	Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content.
27	0.324076	true	strings	Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
34	0.672978	false	these	Falcon Heavy is the largest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
83	0.805673	false	these	Brexit is a reversible decision, Sir Mike Rake, the chairman of WorldPay and ex-chairman of BT group, said as calls for a second EU referendum were sparked last week.
-39	0.228597	true	random	We consider some context words as positive examples and sample negatives at random from the dictionary.
-38	0.183408	false	strings	The cat sat on the mat.
61	0.325977	false	random	Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
94	0.169675	true	are	We consider all context words as positive examples and sample negatives at random from the dictionary.
-19	0.603952	false	these	In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings.
74	0.458332	true	are	Most of the graduates of my program have moved on to other things because the jobs suck.
19	0.252149	false	strings	Some of the graduates of my program have moved on to other things because the jobs suck.
-85	0.9867	true	strings	John ate pasta for supper.
-88	0.304956	true	strings	Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally.
15	0.422984	true	are	The new gaming console is affordable.
-15	0.514673	false	these	Considering this definition, it is not surprising to find frequent use of sarcastic language in opinionated user generated content.

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