In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword | 
| age | old | new | 
| altitude | low | high |
| area | small | vast | 
| brightness | dark | light | 
| clarity | obscure | clear | 
| cleanness | dirty | clean | 
| complexity | simple | complex | 
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |  
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse | 
| hardness | soft | hard | 
| length | short | long | 
| magnitude | small | large | 
| mass | small | large | 
| odor | weak | strong | 
| pressure | low | high | 
| resistance | low | high | 
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large | 
| sound | quiet | loud | 
| sound pitch | low | high | 
| speed | slow | fast | 
| stability | unstable | stable | 
| strength | weak | strong | 
| temperature | low | high | 
| texture | smooth | rough | 
| thermal conductivity | low | high |
| thickness | thin | thick | 
| volume | small | large |
| weight | light | heavy | 
| width | narrow | wide | 
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |


Example Input: Context Word: Dinner.
Example Output: Sentence 1: She prefers to use ceramic over plastic cups for her official dinners, because the _ cups look more expensive. 
Answer1: ceramic. 
Sentence 2: She prefers to use ceramic over plastic cups for her official dinners, because the _ cups look more cheaper. 
Answer2: plastic.

Example Input: Context Word: broke.
Example Output: Sentence 1: Jan broke up with her boyfriend because of his drinking but not his gambling, as she found the _ to be upsetting. 
Answer1: drinking. 
Sentence 2: Jan broke up with her boyfriend because of his drinking but not his gambling, as she found the _ to be entertaining. 
Answer2: gambling.

Example Input: Context Word: bike chain.
Example Output:
Sentence 1: The bike was in the shop to fix the bike chain and they found other issues while at the _ . 
Answer1: shop. 
Sentence 2: The bike was in the shop to fix the bike chain and they found other issues with the _ . 
Answer2: bike.