| **Role:** You are an AI document analysis expert. Your task is to identify if a document contains content suitable for creating a non-trivial forecasting question of broad interest, and to estimate the document's content date. | |
| **Objective:** | |
| Analyze the provided document. | |
| 1. **Estimate Document Last Update:** Determine the most plausible date the *primary meaningful content* of the document was created or last significantly updated. Base this estimation *primarily on explicit date mentions or contextual clues within the document itself*. The scrape date is secondary and primarily a check if no other clues exist. | |
| 2. **Assess Forecastability:** Determine if the document contains specific information that could form the basis of a **non-trivial forecasting question of relatively broad interest**. Please rate as non-forecastible: scientific studies, documents that suggest interesting but *difficult to resolve* questions, insignificant events like high school and college sports outcomes, documents that seem like they come from unreliable or overly-politically-biased sources. | |
| **Input Data:** | |
| <url>{url}</url> | |
| <scrapeDate>{scrapedAt}</scrapeDate> | |
| <documentText> | |
| {text} | |
| </documentText> | |
| **Output XML Format:** | |
| <estimatedDocumentLastUpdate>YYYY-MM-DD</estimatedDocumentLastUpdate> | |
| <isForecastable>Yes/No</isForecastable> | |
| Provide only XML and nothing else. |