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>
Jaguar XJR-15 The Jaguar Sport XJR-15 is a two-seater sports car produced by JaguarSport, a subsidiary of Jaguar and Tom Walkinshaw Racing between 1990 and 1992. Only 53 were made, each selling for GB£500,000. The chassis was mechanically based on the Le Mans-winning XJR-9, designed by Tony Southgate. The body of the XJR-15 was designed by Peter Stevens, who went on to co-design the McLaren F1. The car competed in a single-make racing series called the Jaguar Intercontinental Challenge, which supported three Formula 1 races (Monaco, Silverstone and Spa) in 1991. The XJR-15 was the world's first road-car made entirely from carbon-fibre. History Tom Walkinshaw conceived the concept in 1988 after seeing the XJ220 concept at the British Motor Show. Following Jaguar's success at Le Mans, he enlisted Peter Stevens to develop a road-going version of the XJR-9, originally designated the R-9R. A number of wealthy racing enthusiasts were keen to own such a car and pressed Walkinshaw into manufacturing a 'road going racer'. This car was originally intended to be a better alternative to the XJ220. Original owners included Derek Warwick, Bob Wollek, Vern Schuppan, Matt Aitken, Andy Evans and the Sultan of Brunei. In order to adapt the XJR-9 for road use, Stevens made a number of modifications to increase space and improve access. "Taking the race car as a base, we widened the cockpit by and raised the roof by to allow more headroom", he said when interviewed in 1991. "The scale model was ready by Easter 1989, from there we went to clay... which was finished by October (1989). The first prototype was held up by Le Mans preparations but it was ready for Tom (Walkinshaw) to drive when he came back from France in July 1990". TWR explicitly developed the XJR-15 as a road-going racing car, in the mould of the Jaguar C and D types, the Ford GT40 and the Ferrari 250 GTO. As such, the car complied with British construction and use regulations and could be registered by the owner for road-use in the UK, although with such a limited production run, the car was never type-approved. The car's production was announced in a press release on 15 November 1990 with an official launch at Silverstone early in 1991. The XJR-15 was built by JaguarSport in Bloxham, Oxfordshire, (a subsidiary of TWR; it was a joint venture between Jaguar Cars and TWR to produce high performance sports cars) England from 1990 to 1992 and had no official involvement from Jaguar itself. Design The mid-engine, rear-wheel drive sports car is powered by a , naturally aspirated 24-valve V12 engine of 5993 cc, with a Group C bottom-end and Group A top-end. The engine features an advanced electronically managed fuel injection system with a very advanced (for its time) 'fly by wire' throttle. Transmission is via a TWR six-speed manual, unsynchronized transmission (a five-speed, synchromesh transmission was also available as an optional extra). The XJR-15's chassis and bodywork are composed of carbon fibre and Kevlar (XJR-15 was the first road-going car built entirely of carbon and Kevlar composites, before the McLaren F1 used similar techniques in 1992). It was designed to comply with 1990 Group C regulations, being 480 cm long, 190 cm wide and 110 cm high. At , the XJR-15 weighed about the same as a contemporary VW Golf. Suspension is fully independent, with non-adjustable Bilstein shock absorbers all round. Front suspension is by wide-based wishbones, working push-rods to spring damper units mounted horizontally across the centre of the car. TWR racing practice is also followed at the rear, with vertical coil-springs mounted
</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.