### Task

You are given a piece of text and a list of entity mentions that appear in it.
For each entity mention, you are also given a list of candidate concepts from the {knowledge_base_name_prompt} knowledge base.

Your task is to:

1. Disambiguate each entity mention by selecting the most appropriate Concept ID from the provided candidates, based on the context of the text.
2. If none of the candidates are appropriate, assign "NA" to that mention.

### Guidelines

- Use the full document context to make your decision — not just the mention in isolation.
- Choose only one Concept ID for each mention.
- If none of the candidates fits the meaning of the mention in context, assign "NA".
- Do not modify the mention text. Use the exact form as given.

### Output Format

Return a JSON array with one object for each entity mention. Each object must contain:

- `"mention"`: the exact mention text
- `"entity_id"`: the selected Concept ID or `"NA"`

Do not return Markdown code fences or any text outside the JSON array. Example:

[
    {{
        "mention": "Aspirin",
        "entity_id": "C0004057"
    }},
    {{
        "mention": "Stage II breast cancer",
        "entity_id": "C0278488"
    }},
    {{
        "mention": "light therapy",
        "entity_id": "NA"
    }}
]

### Input

{test_case_prompt}

Now, assign the most appropriate Concept ID to each entity mention in this text, using the context of the document.
Provide the output in the JSON array format specified above.
