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>
Chiisagata District, Nagano is a district located in Nagano Prefecture, Japan. Population As of February 1, 2006, the district has an estimated population of 12,039. The total area is now down to 241.04 km². There are only one town and one village left in the district: Aoki and Nagawa. History January 14, 1879 - Due to the district, ward, town and village status enforcement, the district seat was located at the town of Ueda. April 1, 1889 - Due to enforcing the town and village status, Chiisagata District formed the towns of Ueda, Nagakuboshin, and Nagakubofuru, and 32 villages (3 towns, 32 villages) October 30, 1912 - The village of Maruko gained town status. (4 towns, 31 villages) May 1, 1919 - The town of Ueda gained city status which lasted until March 6, 2006. (3 towns, 31 villages) September 10, 1921 - (-) The village of Sakashita merged into the city of Ueda. (3 towns, 30 villages) September 1, 1949 - The villages of Higashishiota and Fujisan merged to form the village of Higashishiota. (3 towns, 29 villages) October 1, 1953 - The village of Sagata gained town status and changed the name to Tanaka. (4 towns, 28 villages) April 1, 1954 - (-) The villages of Shiojiri and Kawabe merged into the city of Ueda (4 towns, 26 villages) October 1, 1954 - The villages of Higashiuchi and Nishiuchi merged into the town of Maruko (4 towns, 24 villages) April 1, 1955 - The villages of Yoda and Nagase merged into the town of Maruko. (4 towns, 22 villages) May 1, 1956 - The villages of Nishishiota, Bessho, Higashishiota, and Nakashiota merged to form the town of Shiota. (5 towns, 18 villages) September 30, 1956 (4 towns, 11 villages) The town of Tanaka and the villages Netsu and Wa merged to form the town of Tōbu. The village of Toyosato and Tonoshiro merged to form the village of Toyotono. The towns of Nakakuboshin and Nakakubofuru and the village of Daimon merged to form the town of Nagato. (-) The villages of Kamigawa and Izumida merged into the city of Ueda. The village of Shiokawa merged into the town of Maruko March 31, 1957 (4 towns, 10 villages) Parts of the village of Urazato merged into the village of Aoki. The village of Muroga and the remaining parts of the village of Urazaro merged to form the village of Kawanishi. August 1, 1957 - (-) The village of Kamishina merged into the city of Ueda (4 towns, 9 villages) April 1, 1958 - (-) The village of Toyotono merged into the city of Ueda (4 towns, 8 villages) April 10, 1958 - The village of Shino merged into the town of Tōbu. (4 towns, 7 villages) October 1, 1958 - The villages of Naga, Hoyo, and Motohara merged to form the town of Sanada. (5 towns, 4 villages) April 1, 1959 - (-) Parts of the town of Tōbu was merged into the city of Komoro. April 1, 1970 - (-) The town of Shiota was merged into the city of Ueda.(4 towns, 4 villages) April 1, 1973 - (-) The village of Kawanishi was merged into the city of Ueda.(4 towns, 3 villages) April 1, 2004 - (-) The town of Tōbu merged with the village of Kitamimaki from Kitasaku District to form the new city of Tōmi.(3 towns, 3 villages) October 1, 2005 - The town of Nagato and the village of Wada merged to form the new town of Nagawa.(3 towns, 2 villages) March 6, 2006 - (-) The towns of Maruko and Sanada, and the
</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.