System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Logical Robustness: Does the model ensure general applicability and avoid logical contradictions in its reasoning steps for an instruction that requires step-by-step logical process? This includes the consideration of edge cases for coding and mathematical problems, and the absence of any counterexamples.
Score 1: The logic of the model's response is completely incoherent.
Score 2: The model's response contains major logical inconsistencies or errors.
Score 3: The model's response contains some logical inconsistencies or errors, but they are not significant.
Score 4: The model's response is logically sound, but it does not consider some edge cases.
Score 5: The model's response is logically flawless and it takes into account all potential edge cases.
Metacognition: Did the model respond with awareness of its own capability? Did the model acknowledge the uncertainty in ambiguous or uncertain instructions, and disclose its limitations when it lacked the necessary information or limited capability to provide a reliable response?
Score 1: The model incorrectly responds to ambiguous or uncertain instructions with confidence.
Score 2: The model attempts to respond to ambiguous or uncertain instructions without explicitly acknowledging its uncertainty or limitations.
Score 3: The model does not respond to ambiguous or uncertain instructions but also does not explicitly acknowledge its uncertainty or limitations.
Score 4: The model attempts to respond to ambiguous or uncertain instructions but does explicitly acknowledge its uncertainty and limitations.
Score 5: The model avoids responding to ambiguous or uncertain instructions and explicitly acknowledges the uncertainty of its response, disclosing its limitations when it lacks the necessary information for a reliable response.
Commonsense Understanding: Is the model accurately interpreting world concepts for instructions that require a simulation of the expected result or necessitate commonsense or spatial reasoning?
Score 1: The model completely misinterprets world concepts or misunderstands commonsense knowledge.
Score 2: The model misinterprets crucial world concepts, potentially leading to misinformation.
Score 3: The model shows a few errors in its understanding of world concepts.
Score 4: A single, minor error exists in the model's comprehension of world concepts.
Score 5: The model accurately interprets world concepts without any errors.
[Instruction]
In this task, you'll be provided two sentences. You should classify the relationship between the two sentences either 'entailment' or 'neutral'.\n\nSentence 1: A not so tall person reading a paper is not currently sitting inside a cathedral.\nSentence 2: A not so tall person reading a paper is not currently sitting inside a building.

[Ground truth Answer]
neutral

[Assistant's Response]
To classify the relationship between the two sentences provided, we need to analyze the logical connections between them.

**Sentence 1:** A not so tall person reading a paper is not currently sitting inside a cathedral.

**Sentence 2:** A not so tall person reading a paper is not currently sitting inside a building.

The key point to consider is the definition of a cathedral in relation to a building. A cathedral is a specific type of building; therefore, if someone is not sitting inside a cathedral, it is possible that they could still be sitting inside another type of building. The negation in Sentence 1 does not imply the negation in Sentence 2. 

Thus, while Sentence 1 states that the person is not in a cathedral, it does not provide enough information to conclude that they are also not in any building at all. This leads us to classify the relationship between the two sentences as **'neutral'**. 

In summary, the relationship is neutral because the first sentence does not entail the second; the absence of being in a cathedral does not logically lead to the absence of being in a building.

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant: