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>
(FTP-NEA), and roughly half the FEA's original members joined it. Collective bargaining and conflict Despite the fragmentation of the FEA, teachers in Florida still were able to achieve a major collective bargaining victory. The militancy of the teachers' unions in Florida, combined with continuing concern over the 1968 strike, prompted the Florida state legislature in 1974 to enact a public employee collective bargaining law. Pat Tornillo helped draft the bill. Tornillo quickly came to control FEA-United. Although he was not elected president of the federation until 1978, a position he held until 2000, he was the dominant force within the new AFT state federation. In 1981, he was elected a vice president of the AFT and sat on the AFT executive council's influential executive committee. Under Tornillo, FEA-United proved to be very influential within the Florida AFL-CIO. A quarter of the AFL-CIO's state membership belonged to FEA-United, and the union began exercising its political muscle. In 1993, FEA-United, working with AFCSME, unseated 16-year incumbent state AFL-CIO president Danny Miller. With FEA-United's support, the post was won by Marilyn Lenard, president of the Space Coast Labor Council and a CWA member. However, conflict between FEA-United and FTP-NEA continued. In March 1983, the AFT successfully raided the FTP-NEA's large Broward association, The Classroom Teachers Association (CTA). The AFT had forced an election for a new bargaining representative three times between 1975 and 1979 but had failed to win the elections. After the 1983 victory, Tony Gentile, a veteran AFT activist who had been president since 1979, became the new bargaining agent for Broward's teachers.. In 1990, the AFT also successfully raided the Volusia Education Association, another large FTP-NEA local. In addition to raiding, both organizations also organized new members. For example, in 1990 FEA-United successfully organized a unit of about 450 blue-collar workers in the Hernando County school district. In 1998, full-time faculty at Miami-Dade Community College also voted to join FEA-United. In fact, during the 1980s both state unions put a high priority on organizing education support professionals across the state. It was during this period that the character of the two organizations changed from being unions that only represented teachers, to representing all categories of public school employees. But there were losses on both sides as well. In 1980, the Hillsborough Classroom Teachers Association, the Collier County Education Association, and the Hendry County Education Association disaffiliated from FEA-United over Tornillo's increasingly dictatorial approach to running the state union, and became independent unions. Four years later all three locals chose to become affiliates of the Florida Teaching Profession-National Education Association. In 1982 the United Faculty of Florida, representing university faculty on all campuses of Florida's State University System, as well as a number of communinity college faculties, switched affiliation from FEA/United to FTP-NEA. In addition, in 1985 the FEA/United affiliate in Charlotte County was defeated by the two new FTP-NEA affiliates and lost the right to represent teachers and support personnel. In 1998, the Sarasota County Classified/Teachers Association—FEA-United's fourth-largest affiliate—voted to become independent as well, arguing that FEA-United had not done enough to service the local's contract. But despite the conflict, the two unions remained remarkably evenly matched. By 1987, FTP-NEA's membership had risen to about 37,000 members, while FEA-United's membership stood at about 30,000 members. By 2000, when the two unions merged, FTP-NEA membership had risen to 60,000 while FEA-United had 45,000. Merger By 1990, FEA-United and FTP-NEA were talking merger. Despite 15 years of competition, neither union had achieved an overwhelming majority among the state's teachers. Worse, the problems confronting the state's schools had not improved much since 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.