FUN TASK : Write a sarcastic paraphrase for a dialogue response and explain the reason for it
We are a group of natural language processing (NLP) researchers from Columbia University, conducting academic research about figurative language understanding. We want to use machine learning to understand and interpret figurative language. Below you will see a social context and a two-turn dialogue containing a previous turn and a response sentence that is LITERAL in nature. Please type in the two separate text boxes the two subtasks 1) a reframing of the literal response in the dialogue that is a SARCASTIC paraphrase of it and 2) The explanation so as to why this sarcasm is appropriate for the literal. Sarcasm refers to the use of words that mean the opposite of what you really want to say, especially in order to insult someone or to show irritation, or just to be funny.
The SARCASTIC reframing should be faithful and consistent to the literal input, congruent to the social context and make sure you use some sort of humor and/or incongruity to your basic commonsense about everyday events and concepts. Please try and be creative and avoid using simple rephrasing or only single-word replacements or just negation. Your explanations should be logical, detailed, and easy to understand. DO NOT COPY THE LITERAL INPUT IN THE BOXES. We will reject hits for such cases.
For example:
Social Context: Remy started to hurt all over and decided to skip going to the doctor looking for self-care.
Previous Turn: The lines could be long.
Response: Last time I waited four hours at my doctor's office.
1. Please write in the text box a SARCASTIC reframing that is faithful and consistent to the literal response:
2. Please write in the text box an explanation for your proposed reframing:
1. Please write in the text boxes a SARCASTIC reframing that is faithful and consistent to the literal response and the explanation for it.
Social Context: ${context}
Previous Turn: ${previous}
Literal Response: ${response}
1. Reframing:
2. Explanation:
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| Qualifications Required: HIT Approval Rate (%) for all Requesters' HITs greater than 99 , Number of HITs Approved greater than 10000 , Location is US |
We are a group of natural language processing (NLP) researchers from Columbia University, conducting academic research about figurative language understanding. We want to use machine learning to understand and interpret figurative language. Below you will see a social context and a two-turn dialogue containing a previous turn and a response sentence that is LITERAL in nature. Please type in the two separate text boxes the two subtasks 1) a reframing of the literal response in the dialogue that is a SARCASTIC paraphrase of it and 2) The explanation so as to why this sarcasm is appropriate for the literal. Sarcasm refers to the use of words that mean the opposite of what you really want to say, especially in order to insult someone or to show irritation, or just to be funny.
The SARCASTIC reframing should be faithful and consistent to the literal input, congruent to the social context and make sure you use some sort of humor and/or incongruity to your basic commonsense about everyday events and concepts. Please try and be creative and avoid using simple rephrasing or only single-word replacements or just negation. Your explanations should be logical, detailed, and easy to understand. DO NOT COPY THE LITERAL INPUT IN THE BOXES. We will reject hits for such cases.
For example:
Social Context: Remy started to hurt all over and decided to skip going to the doctor looking for self-care.
Previous Turn: The lines could be long.
Response: Last time I waited four hours at my doctor's office.
1. Please write in the text box a SARCASTIC reframing that is faithful and consistent to the literal response:
2. Please write in the text box an explanation for your proposed reframing:
1. Please write in the text boxes a SARCASTIC reframing that is faithful and consistent to the literal response and the explanation for it.
Social Context: ${context}
Previous Turn: ${previous}
Literal Response: ${response}
1. Reframing:
2. Explanation:
