dataset_id int64 0 5.5k | category stringlengths 2 27 | instruction stringlengths 19 90 | train_inputs listlengths 381 411 | train_outputs listlengths 381 411 | val_inputs listlengths 89 119 | val_outputs listlengths 89 119 | soft_prompt array 2D |
|---|---|---|---|---|---|---|---|
5,089 | shading | hue, tint, color, tone, shade | ["The artist blended various gradients to create depth in the portrait.","She adjusted the intensity(...TRUNCATED) | ["hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hu(...TRUNCATED) | ["In the sketch, the subtle shifts in brightness created a sense of volume.","She layered different (...TRUNCATED) | ["hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hue","hu(...TRUNCATED) | [[-0.0201416015625,-0.00518798828125,0.0126953125,-0.01165771484375,-0.00518798828125,0.001091003417(...TRUNCATED) |
1,276 | fortify | defend, protect, shield, secure, safeguard | ["The soldiers built a barrier to shield the city from invaders.","She reinforced the walls with ext(...TRUNCATED) | ["defend","defend","defend","defend","defend","defend","defend","defend","defend","defend","defend",(...TRUNCATED) | ["The citizens worked tirelessly to create a bulwark against potential threats.","The strategy invol(...TRUNCATED) | ["defend","defend","defend","defend","defend","defend","defend","defend","defend","defend","defend",(...TRUNCATED) | [[0.001739501953125,-0.009033203125,-0.004730224609375,-0.006622314453125,0.0101318359375,0.01428222(...TRUNCATED) |
5,252 | sprinkler | irrigation, garden, lawn, landscape, agriculture | ["In the early morning, water droplets spread evenly across the garden, nurturing the plants.","The (...TRUNCATED) | ["irrigation","irrigation","irrigation","irrigation","irrigation","irrigation","irrigation","irrigat(...TRUNCATED) | ["The device's nozzles release water in a controlled pattern, preventing waste.","For optimal plant (...TRUNCATED) | ["irrigation","irrigation","irrigation","irrigation","irrigation","irrigation","irrigation","irrigat(...TRUNCATED) | [[-0.0037078857421875,-0.002899169921875,-0.006134033203125,0.0078125,0.006500244140625,0.0190429687(...TRUNCATED) |
1,547 | geometricshape | triangle, polygon, square, oval, circle | ["The three-sided figure was drawn with precise angles and equal-length sides.","In the design, the (...TRUNCATED) | ["triangle","triangle","triangle","triangle","triangle","triangle","triangle","triangle","triangle",(...TRUNCATED) | ["The children learned about a figure with three sides in their math class today.","The logo consist(...TRUNCATED) | ["triangle","triangle","triangle","triangle","triangle","triangle","triangle","triangle","triangle",(...TRUNCATED) | [[0.00994873046875,-0.00360107421875,-0.006072998046875,0.0027313232421875,-0.00848388671875,0.00376(...TRUNCATED) |
485 | biased | discrimination, bigotry, unfairness, preconception, stereotype | ["She noticed that the hiring process seemed to favor certain groups over others, regardless of qual(...TRUNCATED) | ["discrimination","discrimination","discrimination","discrimination","discrimination","discriminatio(...TRUNCATED) | ["Some residents felt that local services were allocated unevenly, benefiting only certain neighborh(...TRUNCATED) | ["discrimination","discrimination","discrimination","discrimination","discrimination","discriminatio(...TRUNCATED) | [[0.00173187255859375,-0.01397705078125,-0.0024871826171875,0.00009441375732421875,-0.01165771484375(...TRUNCATED) |
1,637 | injection | subcutaneous, intramuscular, intravenous, intralesional, intradermal | ["The nurse prepared the site on the patient's arm for the procedure, ensuring it was clean and disi(...TRUNCATED) | ["subcutaneous","subcutaneous","subcutaneous","subcutaneous","subcutaneous","subcutaneous","subcutan(...TRUNCATED) | ["Medical professionals must be trained to perform this technique safely and effectively.","The site(...TRUNCATED) | ["subcutaneous","subcutaneous","subcutaneous","subcutaneous","subcutaneous","subcutaneous","subcutan(...TRUNCATED) | [[-0.015869140625,0.0189208984375,-0.005828857421875,-0.035400390625,-0.01544189453125,0.01007080078(...TRUNCATED) |
4,006 | painkillers | aspirin, acetaminophen, codeine, ibuprofen, naproxen | ["After a long day of gardening, she needed something to ease the throbbing in her joints.","The pha(...TRUNCATED) | ["aspirin","aspirin","aspirin","aspirin","aspirin","aspirin","aspirin","aspirin","aspirin","aspirin"(...TRUNCATED) | ["He had heard that some people use it to prevent blood clots, but he wasn't sure if it was safe.","(...TRUNCATED) | ["aspirin","aspirin","aspirin","aspirin","aspirin","aspirin","aspirin","aspirin","aspirin","aspirin"(...TRUNCATED) | [[0.000885009765625,-0.0135498046875,-0.005279541015625,-0.00787353515625,-0.021728515625,0.02990722(...TRUNCATED) |
438 | emerging | ascending, burgeoning, surging, developing, rising | ["The startup is gaining traction in the market, quickly moving from obscurity to prominence.","New (...TRUNCATED) | ["ascending","ascending","ascending","ascending","ascending","ascending","ascending","ascending","as(...TRUNCATED) | ["The latest trends in fashion are capturing the public's imagination, inspiring new styles.","Advan(...TRUNCATED) | ["ascending","ascending","ascending","ascending","ascending","ascending","ascending","ascending","as(...TRUNCATED) | [[0.01275634765625,-0.0069580078125,-0.0084228515625,0.0018157958984375,-0.0027008056640625,0.012878(...TRUNCATED) |
994 | stains | dust, rust, grease, dirt, grime | ["A thick layer of tiny particles accumulated on the fabric after the long journey.","The carpet had(...TRUNCATED) | ["dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","(...TRUNCATED) | ["The tablecloth bore the marks of many meals, looking dull and uninviting.","A film of dirt obscure(...TRUNCATED) | ["dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","dust","(...TRUNCATED) | [[0.00347900390625,-0.00885009765625,-0.015869140625,0.00494384765625,0.019775390625,0.0091552734375(...TRUNCATED) |
3,400 | drives | motive, force, instinct, impulse, trigger | ["Every morning, she wakes up eager to pursue her daily goals and aspirations.","The team's passion (...TRUNCATED) | ["motive","motive","motive","motive","motive","motive","motive","motive","motive","motive","motive",(...TRUNCATED) | ["Understanding what propels someone to achieve greatness can be fascinating.","Her curiosity about (...TRUNCATED) | ["motive","motive","motive","motive","motive","motive","motive","motive","motive","motive","motive",(...TRUNCATED) | [[-0.0081787109375,0.01080322265625,0.014892578125,0.01153564453125,-0.01190185546875,-0.00389099121(...TRUNCATED) |
End of preview. Expand in Data Studio
Classification-DoD
Licensing and Attribution
This dataset is licensed under the Apache License 2.0.
It is a collection of classification tasks designed for soft prompt mapping experiments.
Features:
- Sentence inputs paired with their corresponding classification labels (keywords).
- Train/Test splits provided per task.
- Includes pre-trained continuous soft prompt embeddings for each task (
soft_promptarray).
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