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
-82	0.752609	true	are	All of the graduates of my program have moved on to other things because the jobs suck.
76	0.503853	false	these	Tom and Adam were whispering in the theater.
84	0.223677	false	random	In example (1) it is quite difficult to see the exaggerated positive sentiment used in order to convey strong negative feelings.
42	0.015708	true	random	We built our society on unclean energy.
-24	0.297637	false	strings	Brexit is an irreversible 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.
-17	0.301032	true	random	We consider many context words as positive examples and sample negatives at random from the dictionary.
-32	0.3172	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.
-75	0.743598	false	are	Pursuing a strategy of protest, Gandhi took the administration by surprise and won concessions from the authorities.
78	0.5391	false	random	Cruz has frequently derided as "amnesty" various plans that confer legal status or citizenship on people living in the country illegally.
-36	0.764927	false	these	House Speaker Paul Ryan was facing problems from fellow Republicans unhappy with his leadership.
-28	0.780361	false	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.
2	0.266342	true	these	Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally.
74	0.557699	true	these	Tom and Adam were whispering in the theater.
-91	0.19041	true	are	Writing Java is not too different from programming with handcuffs.
-90	0.787288	true	random	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.
-98	0.449882	false	these	We built our society on unclean energy.
18	0.255163	true	strings	Writing Java is not too different from programming with handcuffs.
-50	0.207013	true	strings	All animals like to scratch their ears.
53	0.602882	true	strings	Falcon Heavy is the smallest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
24	0.879053	true	are	Cruz has frequently derided as "amnesty" any bill that confers legal status or citizenship on people living in the country illegally.
51	0.472717	true	random	All dogs like to scratch their ears.
-34	0.9043	false	these	John ate pasta for dinner.
-70	0.981872	false	random	We consider some context words as positive examples and sample negatives at random from the dictionary.
-26	0.153973	true	these	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-95	0.164281	true	strings	Cruz has frequently derided as "amnesty" various bills that confer legal status or citizenship on people living in the country illegally.
-52	0.183891	true	random	The cat sat on the mat.
-54	0.577312	false	strings	Notifications about Farmville and other crappy apps 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.
40	0.902709	true	strings	In example (1) it is quite difficult to see the exaggerated positive sentiment used in order to convey strong negative feelings.
64	0.79234	true	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.
7	0.197743	true	random	In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings.
84	0.07592	false	random	We built our society on unclean energy.
20	0.334751	false	these	Adenoiditis symptoms often pass within ten days or less, and often include pus-like discharge from nose.
52	0.739099	false	are	Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally.
-89	0.429253	true	random	Adenoiditis symptoms often pass within ten days or less, and often include pus-like discharge from nose.
91	0.849608	true	these	In many areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
25	0.47167	false	are	We consider all context words as positive examples and sample many negatives at random from the dictionary.
-30	0.747244	false	strings	The villain is the character who tends to have a negative effect on other characters.
72	0.651303	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.
-68	0.435049	false	are	All animals like to scratch their ears.
92	0.337102	false	strings	Falcon Heavy is the largest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
21	0.54952	true	random	In all areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-40	0.221825	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	0.346886	true	strings	We consider some words as positive examples and sample negatives at random from the dictionary.
47	0.616419	true	random	We consider all context words as positive examples and sample many negatives at random from the dictionary.
-76	0.698219	false	these	Falcon Heavy is the largest rocket since NASA's Saturn V booster, which was used for the Moon missions in the 1970s.
22	0.434492	false	random	John ate pasta for dinner.
55	0.245591	true	strings	Tom and Adam were whispering quietly in the theater.
-19	0.074437	false	strings	I can actually see him climbing into a Lincoln saying this.
2	0.927081	false	these	Most of the graduates of my program have moved on to other things because the jobs suck.
-96	0.762039	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.
98	0.590267	true	strings	Brexit is an irreversible 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.
61	0.994968	false	strings	Cruz has frequently derided as "amnesty" any plan that confers legal status or citizenship on people living in the country illegally.
-68	0.005589	false	these	We consider some context words as positive examples and sample negatives at random from the dictionary.
15	0.538465	false	strings	I can actually see him climbing into a Lincoln saying this.
79	0.675474	false	these	In example (1) it is quite difficult to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-43	0.535738	false	strings	John ate pasta for dinner.
39	0.724975	false	strings	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.
-99	0.850307	true	random	In many developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.
-89	0.705522	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 not be unexpected.
-74	0.484564	true	these	Out of the box, Ouya supports Twitch.tv and XBMC media player.
-7	0.761179	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.
44	0.143613	true	these	Tom and Adam were whispering in the theater.
-27	0.161118	true	random	I can actually see him getting into a Lincoln saying this.
38	0.473896	true	strings	John ate pasta for dinner.
80	0.282532	true	are	The cat sat on the mat.
-96	0.687348	false	strings	We consider all context words as positive examples and sample negatives at random from the dictionary.
87	0.828876	true	are	We built our society on unclean energy.
-53	0.961074	false	random	All dogs like to scratch their ears.
-21	0.516863	true	random	The cat sat on the mat.
-62	0.706401	false	are	Tom and Adam were whispering loudly in the theater.
98	0.485793	true	random	I can actually see him climbing into a Mazda saying this.
81	0.87638	false	are	We consider all context words as positive examples and sample negatives at random from the dictionary.
-99	0.733913	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.
-41	0.719152	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.
13	0.523632	false	random	In example (1) it is quite easy to see the exaggerated positive sentiment used in order to convey strong negative feelings.
97	0.222077	false	strings	Most of the graduates of my program have moved on to other things because the jobs suck.
61	0.645225	false	these	House Speaker Paul Ryan was facing problems from fellow Republicans unhappy with his leadership.
-55	0.769117	false	strings	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.
66	0.130606	false	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.
55	0.282973	true	are	Some animals like to scratch their ears.
-27	0.775439	true	are	John ate pasta for dinner.
70	0.345617	true	are	The villain is the character who tends to have a negative effect on other characters.
-82	0.443028	false	strings	In example (1) it is quite straightforward to see the exaggerated positive sentiment used in order to convey strong negative feelings.
-95	0.157135	true	strings	Chicago City Hall is the official seat of government of Chicago.
91	0.548461	false	are	Some dogs like to scratch their ears.
82	0.209688	true	random	The market is about to get harder, but not impossible to navigate.
-55	0.534107	true	random	The market is about to get harder, but not impossible to navigate.
24	0.686677	false	strings	House Speaker Paul Ryan was facing problems uniquely from fellow Republicans supportive of his leadership.
-69	0.748786	false	these	We consider some context words as positive examples and sample negatives at random from the dictionary.
18	0.495991	true	strings	I can actually see him getting into a Lincoln saying this.
35	0.193924	true	these	Writing Java is similar to programming with handcuffs.
-91	0.053784	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.
37	0.023362	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.
-62	0.760876	true	are	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.
0	0.049603	false	random	House Speaker Paul Ryan was facing problems uniquely from fellow Republicans dissatisfied with his leadership.
-1	0.916214	false	strings	Tom and Adam were whispering in the theater.
-58	0.757933	true	are	John ate pasta for breakfast.
-80	0.75554	false	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.
39	0.753771	false	these	John ate pasta for supper.
43	0.847619	true	random	In all developed areas, human activity has changed the form of river channels, altering magnitudes and frequencies of flooding.

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