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>
American League includes more than 30 teams from different universities, including such prominent ones as Harvard, Berkeley and New York University (NYU) (the very first League Champion). KVN Israel comprises two Leagues with about 30 teams from different towns. The U.K. also has a prominent KVN community, with teams from a number of universities. Notable KVN alumni Yuli Gusman, captain of the Guys from Baku team (1967—1971, Major League) and a long-time jury member (since 1986). Gennady Zyuganov, captain of the Physics and Mathematics Faculty team of the Oryol State University (1960s). Leonid Yakubovich, Gennady Khazanov and Vladimir Semago, members of the MISI team (1960s, Major League) and jury. Mikhail Zadornov, captain of the Riga Technical University team (1970s), guest star (2013, Major League). Jury member. Mikhail Yevdokimov, captain of the Novosibirsk Trade University team (1979—1981). Valdis Pelšs, Alexei Kortnev and Neschastny Sluchai, members of the MSU team (1987—1988, Major League) and jury. Leonid Slutsky, The Third Sons team of FC Olimpia Volgograd (1990s), guest star (2013 and 2014, Major League). Jury. Volodymyr Zelensky, President of Ukraine (2019-), captain of Kvartal 95, Kryvyi Rih (1998—2003, Major League). Elchin Azizov, Anar Mammadkhanov and Bahram Bagirzade, members of the Parni iz Baku team (1991—2001, Major League). Pelageya, member of the NGU team (1997, Major League), the youngest KVN player of her time. Jury member. Grigori Gorin and Arkady Arkanov, wrote for the Sechenov University team (1960s). Jury members. Vadim Samoylov of the Agatha Christie rock band, member of the UPI team (1987—1988, Major League). Aleksandr Filippenko, member of the Moscow Institute of Physics and Technology team (1962/1963 champions). Garik Martirosyan and Artur Janibekyan, members of the New Armenians team (1993—2002, Major League). Sergei Svetlakov, member of the Ural pelmeni team (2000—2009, Major League). Petr Elfimov, member of the BSU and RUDN teams (1999—2003, Major League). Sergey Lazarev, captain of the school KVN team (revealed it during one of the games while serving as a jury member). Dmitry Koldun, member of the RSMU team Storm Warning (2005, Euroleague, Premier-League). Also a jury member. Sitora Farmonova, member of the Asia MIX team (2015—2016, Major League). Yolka, member of the united Uzhhorod-Vinnytsia team (2001—2003). Ruben Jaghinyan, member of the Yerevan State Medical University team (1991—1994, Major League). Mikhail Galustyan, member and captain of the Burnt by the Sun team (1999—2003, Major League). Jury member. Semyon Slepakov, captain of the United Pyatigorsk team (2000—2006, Major League). Jury member. Yelena Khanga, member of the World United team (1980s). Anatoly Wasserman, member of the Odessa team (1970s), jury member. References External links some KVN flyers KVN Union official site KVN Western Europe KVN Israel Bearfoot.KVN - All about KVN in Lithuania! American KVN League Category:Russian comedy television series Category:1961 Russian television series debuts Category:1960s Russian television series Category:1970s Russian television series Category:1980s Russian television series Category:1990s Russian television series Category:2000s Russian television series Category:2010s Russian television series Category:2020s Russian television series Category:Russian game shows Category:1960s Soviet television series Category:Soviet television shows
</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.