Expand the initial input questions to incorporate all necessary background context.

--INSTRUCTIONS--
Let's think step by step:

1. STEP 1: For EACH input question, extract the following information:
- period: The relevant period of time for the question, e.g., summer 2024.
- location: The relevant location for the question, e.g., Boston.
- named_entities: A list of named entities, events, or concepts that are relevant to the question.,
- abstract_categories: A comprehensive list of abstract categories that the question falls into, e.g., 'AI technologies', 'healthcare policies', 'education', 'environment', 'security risks', 'safety concerns', 'societal impacts', or similar. Ensure the categories are general and abstract, but not overly broad. Fore example: 'issues' is too broad, 'safety issues' is at the right level of abstraction. Include as many relevant categories as possible.

2. STEP 2: Rewrite each input question to incorporate all necessary context from the background information, period, and place
- Keep the question short and concise.
- Do not telegraph the answer or parts of the answer to the output question. For example, consider this output question: "Given the recent incidents in Zanzibar, what are the health implications of consuming sea turtle meat that have resulted in multiple deaths and hospitalizations?". This is a BAD output question because it telegraphs the answer by mentioning the deaths and hospitalizations as a result of consuming sea turtle meat.
- The output question should ask only one thing at a time rather than having multiple sub-questions. For example, this question is BAD because it contains two sub-questions: ""What recent tragic incidents related to the fentanyl crisis have occurred in Washington and Oregon, and what measures are officials taking in response to these events?".
- All references to people, places, or things should be fully described in the question. Such references should only be included if including this information materially affects the answer.
Ensure that ALL references are clear and unambiguous, e.g., don't refer to "the <entity>", but refer to named or described entities in ways that distinguish them from all other <entities>.
Do this for ALL references, and ensure that all references are absolute (e.g., summer 2024) rather than relative (e.g., this summer).
Examples:
"the proposal" -> "the proposal of the governor of California to increase funding for public schools"
"the meeting" -> "the meeting of Contoso with their new client to discuss the upcoming project"
"the president" -> "the president of the company, John Doe"

--OUTPUT--
Return output as a JSON-formatted object with the following structure:

{
    "questions": [
          {
            "input_question": "The input question that the output question is based on.",
            "period": "The relevant period of time for the question, e.g., summer 2024.",
            "location": "The relevant location for the question, e.g., Boston.",
            "named_entities": "A list of named entities, events, or concepts that are relevant to the question.",
            "abstract_categories": "A comprehensive list of abstract categories that the question falls into, e.g., 'AI technologies', 'healthcare policies', 'education', 'environment', 'security risks', 'safety concerns', 'societal impacts', or similar. Ensure the categories are general and abstract, but not overly broad. Include as many relevant categories as possible.",
            "background_information": "Background information that provides context for the question, e.g., who, what, where, when, why, how, etc.",
            "output_question": "An expanded version of the input question that must stand alone in the absence of the background information. It should incorporate all necessary context from the background information, period, and place without telegraphing the answer to the question. Keep the question short and concise. Avoid questions that contain multiple sub-questions.",
        },
        ...
    ]
}

Output a single JSON list only, with no additional text or commentary.