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>
List of former municipalities of Sweden This list contains some of the defunct Municipalities of Sweden. The total number of municipalities has been reduced from 2,500 in 1863 to 290 today. __TOC__ 1880–1974 These municipalities were merged into others in between the two major municipality reforms in 1952 and 1974. Almunge, merged into Uppsala Municipality 1971 Asarum merged into Karlshamn Municipality 1967 Blidö, merged into Norrtälje Municipality 1971 Boo, merged into Nacka 1971 Brunskogs Municipality, merged into Arvika Municipality och Kil Municipality 1971 Dalarö, merged into Österhaninge Municipality 1959 Dalby, merged into Lund Municipality, 1974 Djursholm, merged into Danderyd Municipality 1971 Djurö, merged into Värmdö 1974 Eds Municipality, merged into Grums Municipality 1969 Ekshärads Municipality, merged into Hagfors Municipality 1971 Finnskoga-Dalby Municipality, merged into Torsby Municipality 1974 Frykeruds Municipality, merged into Kil Municipality 1971 Fryksände Municipality, merged into Torsby Municipality 1967 Frösåker, merged into Östhammar Municipality 1957 Frötuna, merged into Norrtälje Municipality 1971 Färingsö, merged into Ekerö Municipality 1971 Genarps Municipality Gillberga Municipality, merged into Säffle Municipality 1971 Glava Municipality, merged into Arvika Municipality 1971 Grava Municipality, merged into Karlstad Municipality 1971 Gräsmarks Municipality, merged into Sunne Municipality 1971 Grödinge, merged into Botkyrka Municipality 1971 Gunnarskogs Municipality, merged into Arvika Municipality 1971 Gustaf Adolfs Municipality, merged into Hagfors Municipality 1974 Gustavsberg, merged into Värmdö Municipality 1974 Holmedals Municipality, merged into Årjängs Municipality 1971 Hällaryd merged into Karlshamn Municipality 1967 Häverö, merged into Norrtälje Municipality 1971 Järna, merged into Södertälje Municipality 1971 Järnskogs Municipality, merged into Eda Municipality 1971 Klintehamns Municipality, merged into Gotland Municipality 1971 Knivsta, merged into Uppsala 1971 (recreated 2003) Knutby, merged into Uppsala och Norrtälje 1971 Kroppa Municipality, merged into Filipstad Municipality 1971 Kvillinge Municipality, merged into Norrköpings Municipality 1971 Kävlinge köping (1946–1971), changed name to Kävlinge Municipality Köla Municipality, merged into Eda Municipality 1971 Lysviks Municipality, merged into Sunne Municipality 1971 Mörrum merged into Karlshamn Municipality 1967 Norra Ny Municipality, merged into Torsby Municipality 1974 Norra Råda Municipality, merged into Hagfors Municipality 1974 Nors Municipality, merged into Karlstad Municipality 1971 Nyeds Municipality, merged into Karlstad Municipality 1971 Nätra Municipality, merged into Örnsköldsvik Municipality 1971 Rämmens Municipality, merged into Filipstad Municipality 1971 Silleruds Municipality, merged into Årjäng Municipality 1971 Stavnäs Municipality, merged into Arvika Municipality och Grums Municipality 1969 Stora Kils Municipality, merged into Kils Municipality 1971 Stora Sunne Municipality, merged into Sunne Municipality 1963 Svanskogs Municipality, merged into Säffle Municipality 1971 Södra Sandby Municipality Torns Municipality (1952–1967) Töcksmarks Municipality, merged into Årjängs Municipality 1974 Ulleruds Municipality, merged into Forshaga Municipality 1971 Ullvätterns Municipality, merged into Storfors Municipality 1967 Veberöds Municipality Visnums Municipality, merged into Kristinehamns Municipality 1971 Vitsands Municipality, merged into Torsby Municipality 1967 Värmlandsbergs Municipality, merged into Filipstad Municipality 1971 Värmlandsnäs Municipality, merged into Säffle Municipality 1971 Väse Municipality, merged into Karlstad Municipality and Kristinehamns Municipality 1971 Västerhaninge, merged into Haninge Municipality 1971 Åkerbo Municipality, merged into Linköping Municipality 1971 Älgå Municipality, merged into Arvika Municipality 1971 Österhaninge, merged into Haninge Municipality 1971 Östmarks Municipality, merged into Torsby Municipality 1971 Östra Fågelviks Municipality, merged into Karlstad Municipality 1967 1952 This is a partial list of the municipalities that were merged into others as part of the municipal reform of 1952. Alsters Municipality, merged into Nyeds Municipality Bjurtjärns Municipality, merged into Ullvätterns Municipality Blomskogs Municipality, merged into Holmedal Municipality Boda Municipality, merged into Brunskog Municipality Bogens Municipality, merged into Gunnarskog Municipality Borgviks Municipality, merged into Eds Municipality Botilsäter Municipality, merged into Värmlandsnäs Municipality Brattfors Municipality, merged into Värmlandsberg Municipality Bro Municipality, merged into Värmlandsnä Municipality Elleholm merged into Mörrum Municipality Eskilsäters Municipality, merged into Värmlandsnä Municipality Dalby Municipality, merged into Finnskoga-Dalby Municipality Färnebo Municipality, merged into
</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.