You are an AI assistant tasked with analyzing a passage of text to insert retrieval tokens and identify Prefix-intent (PI) and Key Factual Information (KFI). A Prefix-Intent (PI) should be a piece of text that should precede factual information, it must not be only 1 or 2 words. Key Factual Information (KFI) should be meaningful and include important details.

Your goal is to insert a  <|retrieval|> token after it is clear what the intent of the text is (e.g., "The president of the USA is"), but  before the key factual information is stated (e.g., "Joe Biden"). Whenever there is a <|retrieval|> token, we will retrieve the key factual information.

Here is the passage you will be working with:

<passage>
Eddie Massengill 2003 - Eddie Massengill 2004 - Freddie Query 2005 - Freddie Query Pro Late Models 2009 - Cooper Faassen 2010 - Colt James Late Model Stock Cars 1988 - Freddie Query 1989 - Jack Sprague 1990 - Freddie Query 1991 - Freddie Query 1992 - Freddie Query 1993 - Greg Pope 1994 - Jack Sprague 1995 - Greg Pope 1996 - Lance Moss 1997 - Mike Herman Jr. 1998 - Mike Herman Jr. 1999 - Kevin Love 2000 - Kevin Love 2001 - Kevin Love 2002 - Chris Beach 2003 - Shaun Mangum 2004 - Todd Bardburry 2005 - Travis Sharpe 2006 - Shane Brafford 2007 - Chuck Crump 2008 - Kevin Love 2009 - Steve Ackerly 2010 - Jay Payne 2011 - Bobby Measmer Jr. 2012 - Kenny Brooks Late Model Sportsman 1997 - Terry Brooks Limited Late Models 2004 - Terry Brooks Jr. 2005 - Terry Hoggard 2006 - Ben Hinson 2007 - Bobby Measmer Jr. 2008 - Mike Terry Pro Truck 2001 - Roger Lee Newton 2002 - Terry Brooks Jr. 2003 - Terry Brooks Jr. Limited Stock 2001 - Kenneth Cook 2002 - Jeff Melton 2003 - David Kepley Pure Stock 2003 - Mark Harris 2004 - Luke Nickels 2005 - Brian Love 2006 - Steve Irvin 2007 - Ben Smith 2008 - Charles Hutto 2009 - Jeff Melton 2010 - Jeff Melton Street Stock 1997 - Dave Berry 1999 - Mike Glover Fast & Furious Fours 2007 - Tracy Mullis 2008 - Chad Miller 2009 - Wayne Harrington 2010 - Chad Miller Mini Stocks 1997 - David Pennell 2001 - Jeff Whitley 2002 - Roy Maness 2003 - Randy Freeze 2004 - Adam Beaver 2005 - David Pennell Hornets 2002 - Mark Harris 2003 - Mark Harris 2004 - Chad Miller 2005 - Bobby Measmer Jr. Thunderstox 2010 - Rusty Drye INEX Thunder Roadsters 2004 - Matt Lassiter 2005 - Kyle Beattie 2009 - Adam Welch X-Carz 2001 - Guy Bacelo 2002 - Junior Cress In popular culture Concord was noted for being used as a filming & production location, especially within the racing industry given the close proximity to most NASCAR teams. Some of the notable movies & shows filmed at the facility included: 3: The Dale Earnhardt Story & Shaq Vs. (as the opening show of season 2 where Shaquille O'Neal held a match race with NASCAR star & former Concord regular Dale Earnhardt Jr.) Many commercials were filmed at Concord as well, among the companies & brands that used the track included: Allstate, AAA Insurance, Blimpie, Coors Light, ESPN, Gilette, National Guard, Mountain Dew, Pizza Hut, TBS (promotion featuring country music duo Brooks & Dunn for the Coca-Cola 600 in 1998) & Wrangler Jeans. Among video games, Concord was included in several video games. Most notably of those is iRacing.com - which was one of their first tracks that the group laser scanned in 2005. The track is currently a part of iRacing's base content package. It was also featured in the USAR Hooters Pro Cup game by Infogrames (released in 2002 for the PC). Among modding circles for various PC racing games, it was also recreated for several Papyrus NASCAR games such as NASCAR Racing 2003 Season, and also for NASCAR Heat. Concord was also used for some inspiration for a fictional track in several NASCAR console games by EA Sports. The fictional track - called Levi Strauss Signature Speedway debuted in NASCAR 2005: Chase for the Cup References Plemmons, Mark (July/August 2009) Family-friendly, "grassroots racing" is going on all summer long at Concord Speedway. Cabarrus Living Magazine, p.
</passage>

Follow these steps to complete the task:

1. Inserting retrieval tokens:
   a. Read through the text carefully.
   b. Identify potential Prefix-Intent (PI) sections that consist of a single intent and could serve as a search query. You must not modify the prefix intent and it MUST be part verbatim in the passage. It cannot be single or only a few words.
   c. For each identified PI, evaluate if the following sentence/subsentece that could serve as Key Factual Information (KFI).
   d. Insert <|retrieval|> tokens into the text AFTER the Prefix Intent (PI) and BEFORE key factual information is stated (KFI).
   e. Key Factual information should not intersect with Prefix Intent.

2. Identifying Prefix-Intent (PI) and Key Factual Information (KFI):
   a. For each <|retrieval|> token you've inserted, identify the preceding text as the Prefix-Intent (PI).
   b. Identify the following text, up to the next PI, as the Key Factual Information (KFI).
   c. Ensure that both PI and FI are short subsentences or phrases but not 1 or 2 words.

3. Insert <|start-PI|>,<|end-PI|>, <|start-KFI|>, <|end-KFI|>.
   a. For each identified Prefix Intent (PI), add a start and end special tokens (<|start-PI|>,<|end-PI|>) to quickly identify them.
   b. Do the same for the Key Factual Information (KFI) (<|start-KFI|>, <|end-KFI|>)
   c. Ensure that the very first PI in the passage is preceded by <|start-PI|>.
   d. Double-check that every PI and KFI is properly enclosed in these tags.

4. Describing ideal retrieved information:
   a. Given the Prefix-Intent (PI) and Key Factual Information (KFI), imagine an ideal retriever and enormous corpus. 
   b. Using the retriever and corpus, imagine that you can retrieve information given the Prefix-Intent.  
   c. Describe how that content should look like so it helps generating the Key Factual Information (KFI)


5. Reformulate the Prefix Intent if necessary: Reformulate it to not be impersonal. This means that if the subject it is not identified (e.g. it, he, she) you need to add the appropriate subject so the prefix-intent can be understood by itself. The subject should be changed from the previous information in the passage. Reformulated Prefix should not add any extra information or intent that is not mentioned in the original Prefix Intent.


6. Output format:
   For each pair of Prefix-Intent (PI) and Key Factual Information (KFI) you identify, provide the following output separating each example in a JSON list output. Ensure that it is actually a JSON.

   - Prefix_intent: [Write the Prefix Intent here]
   - Prefix_reformulated: [Write the Prefix Intent reformulated]
   - Key_Factual_Information: [Write the Key Factual Information here]
   - Verification: [Confirm that the KFI can be directly derived from the PI given a strictly connected context]
   - Ideal_Knowledge: [Describe how the ideal retrieved content should look to generate the KFI]
   - Explanation: [Briefly explain how the PI and KFI connect and why you chose to insert the <|retrieval|> token in that position]


7. Final step:
   After you have completed the analysis and provided outputs for all identified PI-KFI pairs, present the original passage with the <|retrieval|> tokens inserted in their appropriate positions

Here's an example of the expected output format:

Passage: Girmal Falls General This waterfall extends to a height of up to 100 feet, making it the highest waterfall of Gujarat. The picturesque beauty of this site makes it popular among visitors and people of the region alike. The water swiftly falls from a great height, creating a fog like condition that’s eye catching. The government of this state is working on many projects to make this place an ideal picnic spot and a tourist attraction. The fall comes to its best form at the time of monsoon and provides an immensely striking appearance. Some of the best natural features of Gujarat can be explored in this place. This place is a nice and refreshing retreat for any traveler.

```json
{ "results" : [
  {
    "Prefix_intent": "Girmal Falls General This waterfall extends to a height of up to",
    "Prefix_reformulated": "What is the height of Girmal Falls?",
    "Key_Factual_Information": "100 feet, making it the highest waterfall of Gujarat",
    "Verification": "The KFI directly provides the height information requested in the PI.",
    "Ideal_Knowledge": "A list of waterfalls in Gujarat, India, with their heights and rankings, specifically mentioning Girmal Falls as the highest at 100 feet.",
    "Explanation": "The PI introduces Girmal Falls and sets up a query about its height, while the KFI provides the specific measurement and its significance. The <|retrieval|> token is inserted to indicate where additional information might be needed to support the factual statement."
  },
  {
    "Prefix_intent": "The water swiftly falls from a great height, creating",
    "Prefix_reformulated": "What does the water falling from Girmal Falls create?",
    "Key_Factual_Information": "a fog like condition that's eye catching",
    "Verification": "The KFI directly describes the effect created by the falling water, as prompted by the PI.",
    "Ideal_Knowledge": "Detailed descriptions of the visual effects created by high waterfalls, including the formation of mist or fog-like conditions due to water droplets in the air.",
    "Explanation": "The PI describes the water falling and sets up a query about its effect, while the KFI provides the specific visual phenomenon created. The <|retrieval|> token is inserted to indicate where additional information might be needed to support the description."
  },
  {
    "Prefix_intent": "The fall comes to its best form at the time of",
    "Prefix_reformulated": "When does Girmal Falls come to its best form?",
    "Key_Factual_Information": "monsoon and provides an immensely striking appearance",
    "Verification": "The KFI directly answers when the waterfall is at its best and describes its appearance, as prompted by the PI.",
    "Ideal_Knowledge": "Information on the seasonal variations of Girmal Falls, highlighting the monsoon season's impact on water flow and visual appeal.",
    "Explanation": "The PI sets up a query about the best time to view the falls, and the KFI provides the specific season and describes the appearance. The <|retrieval|> token is inserted to indicate where additional information about seasonal changes might be needed."
  }],
"Updated_Passage":"<|start-PI|> Girmal Falls General This waterfall extends to a height of up to <|end-PI|> <|retrieval|> <|start-KFI|> 100 feet, making it the highest waterfall of Gujarat <|end-KFI|>. The picturesque beauty of this site makes it popular among visitors and people of the region alike. <|start-PI|> The water swiftly falls from a great height, creating <|end-PI|> <|retrieval|> <|start-KFI|> a fog like condition that’s eye catching <|end-KFI|>. The government of this state is working on many projects to make this place an ideal picnic spot and a tourist attraction. <|start-PI|> The fall comes to its best form at the time of <|end-PI|> <|retrieval|> <|start-KFI|> monsoon and provides an immensely striking appearance <|end-KFI|>. Some of the best natural features of Gujarat can be explored in this place. This place is a nice and refreshing retreat for any traveler."
}

```
8. Final check:
  a. Review the Updated_Passage to ensure all PIs and KFIs are properly tagged.
  b. Verify that the first PI in the passage starts with <|start-PI|>.
  c. Make sure there are no missing or misplaced tags.
 
Remember to analyze the entire passage, identify all relevant PI-KFI pairs, and provide the output for each pair as specified. After completing the analysis, present the original passage with the <|retrieval|> tokens inserted in their appropriate positions as part of a new key in the JSON file. Only Ouput the JSON File.