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>
revealed five notable and well-developed medicanes. A second study in 2013 revealed several additional storms with their formation days and also additional information on Medicanes. A third study, conducted in 2007, revealed additional storms with their formation days. A fourth study from 2013 presented several other cyclones and their days of development. A survey made by EUMETSAT resulted in many more cyclones. Studies undergone by numerous users on a Twitter page named 'Medicane_Centre' have gained recognition by newspapers and reportedly an Egyptian scientist - leading to those individuals being used as a source for medicanes, most recently Medicane Scott, which was named by said users. September 1947 September 1973 18–20 August 1976 26 March 1983 7 April 1984, 29–30 December 1984 14–18 December 1985 January 1991, 5 December 1991 21–25 October 1994 10–13 December 1996 22–27 September 1997, 30–31 October 1997, and 5–8 December 1997 25–27 January 1998 19–21 March 1999, 13 September 1999 10 September 2000, 9 October 2000 27–28 May 2003, 16–19 September 2003, 27–28 September 2003, 8 October 2003 19–21 September 2004, 3–5 November 2004 August 2005, 15–16 September 2005, 22–23 October 2005, * 26–28 October 2005, 14–16 December 2005 9 August 2006 19–23 March 2007 16–18 October 2007, 26 October 2007 June 2008, August 2008, September 2008, 4 December 2008 January 2009, May 2009, twice in September 2009, October 2009 12–14 October 2010, 2–4 November 2010 twice in February 2012, 13–15 April 2012. "Scott", October 2019 11 November 2019 19 January 2020 Climatological statistics There have been 100 recognized tropical-like cyclones in the Mediterranean Sea between 1947 and 2011 from the databases of the Laboratory of Climatology and Atmospheric Environment, University of Athens, and METEOSAT. By steady accrual of reported and recognized occurrences of tropical-like cyclones (Medicanes), the number count reached 82 by 30 September 2018. Unlike most northern hemisphere cyclone seasons, Mediterranean tropical-like cyclone activity peaks between the months of September and January. List of storms, by month </center> The numbers do not necessarily mean that all occurrences of Medicanes have been fetched in particular before the end of the 1980s. With the development (and constant improvement) of satellite-based observations, the number count of clearly identified Medicanes increased from the 1980s onward. There might be an additional impact from climate change in the frequency of the observed Medicanes, but this is not deducible from the data. List of storms, by decade </center> Tropical-like cyclones in the Black Sea On a number of occasions, tropical-like storms similar to the tropical-like cyclones observed in the Mediterranean have formed in the Black Sea, including storms in 21 March 2002, 7–11 August 2002, and 25–29 September 2005. The 25–29 September 2005 cyclone is particularly well-documented and investigated. No known cyclones in the Black Sea have attained hurricane strength. See also Unusual areas of tropical cyclone formation Tropical cyclone effects in Europe European windstorm (fully extratropical) South Atlantic tropical cyclone 1996 Lake Huron cyclone 2006 Central Pacific cyclone Subtropical Cyclone Katie Subtropical Cyclone Lexi Tropical cyclone basins Tropical cyclogenesis References Citations Sources External links European Medicanes Monitoring Center website Mediterranean Tropical Products Page – Satellite Services Division – Office of Satellite Data Processing and Distribution Northeast Atlantic and Mediterranean Imagery – NOAA Category:Tropical cyclone meteorology Category:Global warming and hurricanes Category:Types of cyclone
</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.