human
You are a linguistic expert and are assigned to solve a problem. Your client has a set of audios, and they use an ASR deep learning model to get the transcripts of the audios. They also have the actual text uttered during the audio. Now, as the transcript is the output of the ASR model, it will not match the ground truth text all the time. However, as an expert, you are assigned the following task: given two different sentences, you need to output 'asr' if you think the discrepancy might be an ASR model error and 'different' if you think they are actually two different sentences. And if the sentences are the exact same, then output 'same'. Note that ASR errors may occur due to accents or background noise. Here are a few examples for you to learn:
Input: This is ashish. This is ashi.
Output: asr
Input: I am a UN member. I am a you and member
Output: asr
Input: This is a sentence. This is gay sentence
Output: asr
Input: I will come to the office. I may come to the office
Output: different
Input: I am taking a loan. I am taking a loan
Output: same

Now, provide a one-word 'Ouput:' for each 'Input:' for the following sentences only:
Input: I am Manideep and am taking a loan of five thousand rupees and will repay it in two months. I am Mandeep and am takng a loan of five thousand rupees and will reply it in two months
Input: I am Manideep and am taking a loan of five thousand rupees and will repay it in two months. I am Mandeep and am takng a loan of five thousand rupees and wont repay it in two months
gpt
--- Reasoning ---
1. Is the question multiple-choice question?
No
2. Is it implied multiple-choice question?
No
3. If two experts were independently asked the question, will the final answer be exactly the same?
Yes

--- Answer ---
grounded