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>
I not made of stone, like thee?". Cast Charles Laughton as Quasimodo Sir Cedric Hardwicke as Jehan Frollo Thomas Mitchell as Clopin Maureen O'Hara as Esmeralda Edmond O'Brien as Pierre Gringoire Alan Marshal as Captain Phoebus Walter Hampden as Archbishop Claude Frollo Harry Davenport as King Louis XI Katharine Alexander as Madame de Lys George Zucco as Procurator Fritz Leiber as Old nobleman Etienne Girardot as Doctor Helene Whitney as Fleur de Lys Mina Gombell as Queen of beggars Arthur Hohl as Olivier Curt Bois as Student George Tobias as Beggar Rod La Rocque as Phillippe Spencer Charters as Court clerk Kathryn Adams as Fleur's companion Dianne Hunter as Fleur's companion Siegfried Arno as Tailor Peter Godfrey as Monk (uncredited) Rondo Hatton as Ugly Man (uncredited) Production In 1932, it was reported by The Hollywood Reporter that Universal announced that it would remake the 1923 Hunchback of Notre Dame film with John Huston writing a script and that Boris Karloff would play Quasimodo. Irving Thalberg, who was an uncredited producer in the 1923 film, considered remaking the film in 1934 and even discussed the idea with Charles Laughton. Two years later, Universal regained interest in a remake, with a fan poll being instrumental in influencing the studio in making the film. Ronald Colman, Paul Muni, Fredric March, Lionel Barrymore and Peter Lorre were the choices in the poll and in the end, Universal decided to go with Lorre, even as far as negotiating with the actor to star in the film, but the project never materialized. A year later, Carl Laemmle, Jr. persuaded Metro-Goldwyn-Mayer to buy the property from Universal as a star-vehicle for Muni. Metro refused and sold the rights to RKO, with Pandro S. Berman producing and William Dieterle directing. For this production RKO Radio Pictures built on their movie ranch a massive medieval city of Paris and Notre Dame Cathedral in the San Fernando Valley. This was one of the largest and most extravagant sets ever constructed. Screenwriter Sonya Levien, who was entrusted to translate Hugo's novel into this film, made the story relevant to the events of the time the film was made: she made the obvious parallel between Paris' persecution of the gypsies and Germany's treatment of the Jews prior to World War II. Casting After hearing the news that RKO was going to remake the 1923 film, Lon Chaney, Jr. sought to play the role of Quasimodo and screen-tested for the studio. While the studio felt that Chaney gave excellent performances in his numerous screen tests, other actors would be more suitable for the part, Orson Welles being one of the many considered. Laughton was set to star as Quasimodo, but RKO offered Chaney the role when it seemed like the British actor would be unable to work in America due to troubles with the IRS. Laughton managed to overcome his problems and got the part. Pleased with her work on Alfred Hitchcock's Jamaica Inn, Laughton brought a then 18-year old Maureen O'Hara to Hollywood to play Esmeralda. This marked O'Hara's American screen debut. According to actress Kathryn Adams, she was supposed to play Esmeralda, but lost the role to O'Hara when Laughton cabled from Ireland to Hollywood that he was "bringing Esmeralda". Adams played a companion of Fleur as compensation for losing the role. Dieterle wanted Claude Rains to play Frollo, but before he agreed to play the part, he had an unexpected encounter with Laughton on the Universal lot in which Laughton was very condescending. Rains, who had mentored Laughton and John Gielgud at the Royal Academy of Dramatic Arts, later remarked
</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.