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  LingOly-TOO benchmark was created by generating up to 6 obfuscations per problem for 82 problems source from original LingOly benchmark.
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  ```python
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- {'question_n': # The question number in the problem
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- 'prompt': # The main text of the question
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- 'subprompts': [
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- {'questionpart_n': # For questions with several sub-parts (e.g. translating several sentences or matching paris of sentences)
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- 'question': # The text of the question part
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- 'answer': # The correct answer
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- 'matches_human_scoring': # Annotation metadata
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- 'fuzzy_matching': # Annotation metadata
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- 'manual_edit': # Annotation metadata
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- }],
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- 'metadata.preamble': # General text from the overall problem that is shared across all questions for that problem
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- 'metadata.context': # Context text that includes important information, you should prepend your prompt with context for solvability
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- 'metadata.obfuscated': # If this example was obfuscated or not
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- 'metadata.obf_num': # Obfuscation counter (unique per problem). This is 0 if unobfuscated
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- 'metadata.overall_question_n': # The problem number
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- 'metadata.obfuscated_question_n': # Concatenation of problem number and obfuscation number
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  }
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  ```
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  LingOly-TOO benchmark was created by generating up to 6 obfuscations per problem for 82 problems source from original LingOly benchmark.
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  ```python
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+ {'question_n': # The question number in the problem
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+ 'prompt': # The main text of the question including preamble, context and previous questions
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+ 'completion': # The correct answer
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+ 'context': # Context text that includes important information, you should prepend your prompt with context for solvability
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+ 'obfuscated': # If this example was obfuscated or not
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+ 'overall_question_n': # The problem number
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+ 'obfuscated_question_n': # Concatenation of problem number and obfuscation number
 
 
 
 
 
 
 
 
 
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  }
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  ```
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