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
94	0.974617	true	random	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.
-15	0.267312	true	are	The market is about to get harder, but not impossible to navigate.
-94	0.697147	false	these	The cat sat on the mat.
-13	0.731366	false	are	The cat did not sit on the mat.
78	0.661775	false	are	Pursuing a strategy of nonviolent protest, Gandhi took the administration by surprise and won concessions from the authorities.
-57	0.596857	false	strings	Cruz has frequently derided as "amnesty" any bill that confers legal status or citizenship on people living in the country illegally.
-14	0.509146	false	strings	Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
-76	0.125491	true	random	Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally.
-78	0.530412	true	these	We built our society on unclean energy.
41	0.58227	false	these	Writing Java is not too different from programming with handcuffs.
93	0.245271	false	random	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.
-46	0.544558	true	strings	Most of the graduates of my program have moved on to other things because the jobs suck.
-62	0.499049	false	are	Cruz has frequently derided as "amnesty" any bill that confers legal status or citizenship on people living in the country illegally.
46	0.133547	true	are	We consider some context words as positive examples and sample negatives at random from the dictionary.
-5	0.285243	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 not be unexpected.
84	0.970523	true	these	We built our society on unclean energy.
-72	0.386024	true	strings	Most of the graduates of my program have moved on to other things because the jobs suck.
-37	0.272609	false	random	The water is too hot.
63	0.791656	true	these	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.
4	0.383718	true	are	We consider some context words as positive examples and sample negatives at random from the dictionary.
85	0.018178	false	are	John ate pasta for dinner.
-59	0.353355	true	are	Tom and Adam were whispering quietly in the theater.
-1	0.242259	true	strings	John ate pasta for breakfast.
-71	0.118438	true	strings	We built our society on clean energy.
-83	0.782141	false	strings	In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-62	0.520389	true	these	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
49	0.880807	true	random	He agreed with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
44	0.838137	false	these	I can actually see him climbing into a Lincoln saying this.
39	0.057426	true	these	He agreed with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
16	0.328421	false	strings	None of the graduates of my program have moved on to other things because the jobs suck.
-39	0.997209	false	random	The new gaming console is unaffordable.
71	0.637125	true	these	We consider some context words as positive examples and sample negatives at random from the dictionary.
60	0.725875	false	random	Most of the graduates of my program have moved on to other things because the jobs suck.
-89	0.865532	true	strings	We consider some context words as positive examples and sample negatives at random from the dictionary.
30	0.440648	false	are	We consider some context words as positive examples and sample negatives at random from the dictionary.
61	0.744661	true	strings	In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings.
53	0.217299	false	strings	House Speaker Paul Ryan was facing problems from fellow Republicans dissatisfied with his leadership.
-65	0.906862	false	random
53	0.926579	false	these	Falcon Heavy is the largest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
75	0.354135	true	are	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.
15	0.375477	false	strings	Cruz has frequently derided as "amnesty" various bills that confer legal status or citizenship on people living in the country illegally.
-10	0.826857	false	random	Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content.
77	0.289575	false	these	And if both apply, they are essentially impossible.
-69	0.035537	false	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.
90	0.445938	false	these	And if both apply, they are essentially impossible.
-15	0.976105	true	are	In example (1) it is quite important to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-4	0.809759	false	strings	In many areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-57	0.493538	false	strings	House Speaker Paul Ryan was facing problems uniquely from fellow Republicans supportive of his leadership.
36	0.293208	true	are	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.
-53	0.126963	true	are	The water is too cold.
-1	0.1682	true	are	I can actually see him climbing into a Mazda saying this.
-71	0.558729	true	these	We built our society on unclean energy.
-58	0.773156	true	these	He agreed with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
-27	0.790437	true	these	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.
-85	0.171423	false	random	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.
39	0.315919	false	random	John ate pasta for supper.
-93	0.583719	true	are	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.
-94	0.019784	false	random	Chicago City Hall is the official seat of government of Chicago.
-69	0.279906	true	random	I can actually see him climbing into a Lincoln saying this.
-91	0.088437	true	strings	Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally.
-76	0.637972	true	are	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
66	0.035189	false	random	If the pipeline tokenization scheme does not correspond to the one that was used when a model was created, it would not be unexpected for it to negatively impact the pipeline results.
-10	0.227084	false	strings	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-43	0.006634	true	these	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.
-92	0.796647	false	strings
40	0.546004	true	strings	House Speaker Paul Ryan was facing problems uniquely from fellow Republicans dissatisfied with his leadership.
-14	0.719664	true	these	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.
62	0.695128	true	random	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-42	0.75118	false	strings	We consider some context words as positive examples and sample negatives at random from the dictionary.
-78	0.807206	false	random	Most of the graduates of my program have moved on to other things because the jobs suck.
27	0.751534	true	these	Adenoiditis symptoms often persist for ten or more days, and often include pus-like discharge from nose.
-49	0.3862	true	these	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.
-95	0.32435	true	strings	Cruz has frequently derided as "amnesty" various bills that confer legal status or citizenship on people living in the country illegally.
6	0.762769	true	strings	Some dogs like to scratch their ears.
41	0.236577	true	random	Adenoiditis symptoms often persist for ten or more days, and often include pus-like discharge from nose.
-69	0.610397	true	these	And if both apply, they are essentially possible.
-94	0.740391	true	strings	I can actually see him getting into a Lincoln saying this.
63	0.704619	true	random	Notifications about Farmville and other crap had become unbearable, then the shift to the non-chronological timeline happened and the content from your friends started to be replaced by ads and other cringy wannabe-viral campaigns.
85	0.952278	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.
-53	0.709851	false	are	Chicago City Hall is the official seat of government of Chicago.
-10	0.980067	false	strings	Pursuing a strategy of violent protest, Gandhi took the administration by surprise and won concessions from the authorities.
68	0.355416	false	these	Pursuing a strategy of protest, Gandhi took the administration by surprise and won concessions from the authorities.
79	0.597238	false	strings	Out of the box, Ouya supports Twitch.tv and XBMC media player.
-70	0.488755	true	strings	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
42	0.293888	false	are	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.
-95	0.616466	false	random	Chicago City Hall is the official seat of government of the City of Chicago.
26	0.014543	true	are	We consider some context words as positive examples and sample negatives at random from the dictionary.
-15	0.958039	true	strings	And if both apply, they are essentially possible.
93	0.566488	true	strings	We consider some words as positive examples and sample negatives at random from the dictionary.
-92	0.924099	true	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.
-69	0.044661	true	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.
-88	0.183979	false	these	In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings.
45	0.679376	true	are	House Speaker Paul Ryan was facing problems from fellow Republicans unhappy with his leadership.
-73	0.304152	true	these	Considering this definition, it is surprising to find frequent use of sarcastic language in opinionated user generated content.
5	0.002751	true	these	We consider some context words as positive examples and sample negatives at random from the dictionary.
-18	0.809915	false	strings	We consider all words as positive examples and sample negatives at random from the dictionary.
32	0.561869	false	strings	In many developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-13	0.562373	false	strings	I can actually see him climbing into a Mazda saying this.
-87	0.175177	true	strings	He agreed with the party's position, but felt that if he resigned, his popularity with Indians would cease to stifle the party's membership.
59	0.871018	true	are	Most of the graduates of my program have moved on to other things because the jobs suck.

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.