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Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-c7a2636c69a747df83ffad5f47fc238f
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-1b47e858aca74da7b06a3c63be3e4609
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-c3a3c1534bf94135a627c972f2e1941b
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-c81659224f0c488b8a0e772f6a1a51fc
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-a454552ea84340c0a040dce8deebaefc
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-8f9fb8a237034bb59de0cf61e8f594c8
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-d5780b6740d347b2bded0dd81dac9fae
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-1f41d2a9c6684c8d9dbd8a120efcbd11
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-58bcb898bbea4f99ae5295804eb65dab
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-257bdf422b714bdfa2a72ed28997d128
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-bf0d7a79e37e47d8a335d878d1d6d619
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-c07a2b7144ab45de872cf63562205e11
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-bda9ecf6cf254a03ac2bccf9881c2fba
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-2728d2fefee746809bf49519b2d04413
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-95055f8ced8e44949cfe7e9bdb514704
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-df1a685a92c048209306469a408fbfae
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-0d2c4d72f6e04d51b8ec9e33b553987b
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-18fbb12c66214eadb32067dbe52e5d18
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-3e03d6a0f071495daa8e25af33ef8c95
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-5cddc821a3b747119032927b9c998067
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-4f9009249d5b4d659106a6f7ab792df4
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-072442c52b76431f985493091ceff395
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-d75940e9cfea4e16855239ff758cc369
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-638c71dba31142309a6ea99e96976696
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-21642eee7d5941929a94614a8629b3bf
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-bdcf3c7674d646be89c77e9f5ff38a05
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-705443e7dfa54b1981189873b163203e
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-2d350149e54f4f6da26868aeca1dfe84
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-2c15c3497b28493fbb77651008ecfd20
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-6d06ff29bb51476dac47679b910bcc5d
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-f8b5434c3d8042b6b7a5da18219faf3c
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-bf8aba2ab10d4cd8809fce46a8b158d4
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-38559cb5abdc42f0b598cedb594f3050
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-aa6c722920bc4df99ec5deadd5855e91
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-fe2997f1aaec4550a1199d642b8c9da2
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-c93be46fc22743c7a2a8c90e5cfc2efe
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-823c596dd3f54bdc9ca57469cb6fd355
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-fe166e3e75ec4f90a1435094089ae5fa
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-79844d7f6e0c45dea3a9c34b077e7890
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-f178f4a364d04cbe92cbd3a02b5816d2
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-12fd9a40e28542ad81d3a432a6cf2150
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-2b9b1500abae47c19adc8c33fb7560ed
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-12a8c99d822a49fc8b253ceb0cd2839b
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-525dabee58db4b01a7479058c0cdbad1
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-c5a11a7ddb4246c5a43d6d459f69f715
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-0979c8a1561a499183f4450cf82dc9c5
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-085e6ee56ac24e97b7b307712b3e4f25
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-dec17925328b47e686ea60edb70184bb
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-092a079e9e084785b5730484e4552ce5
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-73f9879f6b264b62b8370eee2e72a151
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-439ca2633fda492e87aed476b0bea9e5
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-f428d9b61e0b4b98abe2fc83d65d32b0
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-f7750a25c80048feb0a0da93dbc71035
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-c0b38cc14de045fb8d75e153381656b7
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-d075a75dc5a4441da37a119342ed10e6
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-c7f1f2d6a27a40fbbd54769694a580b5
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-b8371a648d504a3a9336359887b65f97
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-f90e2bd3c35c44d3b2032d0e27ee4933
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-82210a82b2ce41a0ad5bda67b3ce3ff2
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-1d828e0ab10f4e588738790038f38dc2
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-c42328d9cc6841d4b3aeb75dcdbdf3f4
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-a4ff3a71070a4052aad67c1cff394668
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-5f7d1830957848a19296198f3e44f6c6
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-666131681d74463fbc7cfe8a705513fa
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-8de5e43496cb4833bdc3bec48d938381
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-963f730f577b47de85bac64fd3691377
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-c7bc7d2b52a34514a40201a24a8bf876
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-2601a0907c4245459174380faa66764d
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-461c6249794c49a39c7b3be6426ba58d
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-304723796bf14e2db495c2e96e4a77e7
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-51a4965c880e4f908c883afeeb353975
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-a32a26c17c794896becedc8fa25d0609
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-d0689e11b9ab448aa494c14cdd9db127
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-25be833d0ddc4738bd84233d570f98a9
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-3a9c191fab914f6b92c268531b9201f8
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-853333e67fc34b0b8b9618defbacf6e0
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-657369c57bbf457ea3e099850f649bcd
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-4a302b7be8e14cfe99670dcc635fd598
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-757741983b3e497ea16bb71ddeb39bcc
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-64b8971f92bd46bb9417c1c78061c835
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-412ae87de4f84b6a912dad6bf4e29c1c
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-d44799c1858b4aaca45305026f6716e3
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-6249da108a9d455fb2024219be91034a
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-46e564ffb70546aea751c2c114405990
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-24de003cac764daf9a85ac49ae9b5255
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-a819f04d283843998a1cbd01db1757e7
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-db911d663ada4b4c8cf0b52a97d000d2
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-cf9ca910399f45ada334e5722f17171d
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-bcf47dbef362472d986b15bc75766245
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-b38e4fb700ab41efa3ce0773eb9582c7
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-f6937acae826471196a9645b7c221eea
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-48c06563b6dc42ddba435e016a4f924a
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-f5a04a0825244709a64365501ceaff02
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-8bfefd18f0ae4dffb116e1999d1a15b4
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-fb6a10643af947498734b96ed3124727
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-94e37a1baf7e429ea3e15fe0e0effd18
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-83b62ee257bb4094866bf9cfbde1a051
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-2c82a14d45fa435a98ddcd9a41aaca9b
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "false" ]
task905-dcf029a364004c9f8c7747c65b58f7c8
Definition: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise. Positive Example 1 - Input: Tweet: "@MarkRoundtreeJr: LMFAOOOO I HATE BLACK P...
[ "true" ]
task905-86e7647b8c1046c98d5334474ae1ebf5
End of preview. Expand in Data Studio

Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task905_hate_speech_offensive_classification

Additional Information

Citation Information

The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:

@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
    title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}, 
    author={Yizhong Wang and Swaroop Mishra and Pegah Alipoormolabashi and Yeganeh Kordi and Amirreza Mirzaei and Anjana Arunkumar and Arjun Ashok and Arut Selvan Dhanasekaran and Atharva Naik and David Stap and Eshaan Pathak and Giannis Karamanolakis and Haizhi Gary Lai and Ishan Purohit and Ishani Mondal and Jacob Anderson and Kirby Kuznia and Krima Doshi and Maitreya Patel and Kuntal Kumar Pal and Mehrad Moradshahi and Mihir Parmar and Mirali Purohit and Neeraj Varshney and Phani Rohitha Kaza and Pulkit Verma and Ravsehaj Singh Puri and Rushang Karia and Shailaja Keyur Sampat and Savan Doshi and Siddhartha Mishra and Sujan Reddy and Sumanta Patro and Tanay Dixit and Xudong Shen and Chitta Baral and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi and Daniel Khashabi},
    year={2022},
    eprint={2204.07705},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2204.07705}, 
}

More details can also be found in the following paper:

@misc{brüelgabrielsson2024compressserveservingthousands,
    title={Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead}, 
    author={Rickard Brüel-Gabrielsson and Jiacheng Zhu and Onkar Bhardwaj and Leshem Choshen and Kristjan Greenewald and Mikhail Yurochkin and Justin Solomon},
    year={2024},
    eprint={2407.00066},
    archivePrefix={arXiv},
    primaryClass={cs.DC},
    url={https://arxiv.org/abs/2407.00066}, 
}

Contact Information

For any comments or questions, please email Rickard Brüel Gabrielsson

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