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>
Terrence Deacon Terrence William Deacon (born 1950) is an American Neuroanthropologist (Ph.D. in Biological Anthropology, Harvard University 1984). He taught at Harvard for eight years, relocated to Boston University in 1992, and is currently Professor of Anthropology and member of the Cognitive Science Faculty at the University of California, Berkeley. Theoretical interests Prof. Deacon's theoretical interests include the study of evolution-like processes at multiple levels, including their role in embryonic development, neural signal processing, language change, social processes, and focusing especially on how these different processes interact and depend on each other. He has long stated an interest in developing a scientific semiotics (particularly biosemiotics) that would contribute to both linguistic theory and cognitive neuroscience. Fields of research Deacon's research combines human evolutionary biology and neuroscience, with the aim of investigating the evolution of human cognition. His work extends from laboratory-based cellular-molecular neurobiology to the study of semiotic processes underlying animal and human communication, especially language and language origins. His neurobiological research is focused on determining the nature of the human divergence from typical primate brain anatomy, the cellular-molecular mechanisms producing this difference, and the correlations between these anatomical differences and special human cognitive abilities, again, particularly language. Work His 1997 book, The Symbolic Species: The Co-evolution of Language and the Brain is widely considered a seminal work in the subject of evolutionary cognition. His approach to semiotics, thoroughly described in the book, is fueled by a career-long interest in the ideas of the late 19th-century American philosopher, Charles Sanders Peirce. In it, he uses the metaphors of parasite and host to describe language and the brain, respectively, arguing that the structures of language have co-evolved to adapt to their brain hosts. His 2011 book, Incomplete Nature: How Mind Emerged from Matter, explores the properties of life, the emergence of consciousness, and the relationship between evolutionary and semiotic processes. The book speculates on how properties such as information, value, purpose, meaning, and end-directed behavior emerged from physics and chemistry. Critics of the book argue that Deacon has drawn heavily from the works of Alicia Juarrero and Evan Thompson without providing full citations or references, but a UC Berkeley investigation exonerated Deacon. In contrast to the arguments presented by Juarrero in Dynamics of Action (1999, MIT Press) and by Thompson in Mind in Life (2007, Belknap Press and Harvard University Press), Deacon explicitly rejects claims that living or mental phenomena can be explained by dynamical systems approaches. Instead, Deacon argues that life- or mind-like properties only emerge from a higher-order reciprocal relationship between self-organizing processes. Bibliography Books The Symbolic Species: The Co-evolution of Language and the Brain. New York: W.W. Norton & Company. 1997. Incomplete Nature: How Mind Emerged from Matter. New York: W.W. Norton & Company. 2011. Articles and essays Deacon, T.W. (1989). "Holism and associationism in neuropsychology: an anatomical synthesis." in E. Perecman (Ed.), Integrating Theory and Practice in Clinical Neuropsychology. Erlbaum. Hilsdale, NJ. 1-47. Deacon, T.W. (1990). "Rethinking mammalian brain evolution." Am Zool. 30:629–705. Deacon, T.W. (1997). "What makes the human brain different?" Annu. Rev. Anthropol. 26: 337-57. Deacon, T.W. (2001). "Heterochrony in brain evolution." In Parker et al. (eds.), Biology, Brains, and Behavior. SAR Press, pp. 41–88. Deacon, T.W. (2006). "Emergence: The Hole at the Wheel’s Hub." Chapter 5 in P. Clayton & P. Davies (Eds.), The Re-Emergence of Emergence: The Emergentist Hypothesis from Science to Religion. Oxford University Press, pp. 111–150. Deacon, T.W. (2006). "Reciprocal linkage between self-organizing processes is sufficient for self-reproduction and evolvability." Biological Theory 1(2):136-149. Deacon, T.W. (2007). "Shannon-Boltzmann-Darwin: Redefining Information. Part 1." Cognitive Semiotics 1:123-148. Deacon, T.W. (2008). "Shannon-Boltzmann-Darwin: Redefining Information. Part
</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.