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>
channel number decreases as T cells are chronically activated. As a result of this differential expression, blockers of KCa3.1 channels preferentially suppress the function of naïve and TCM cells, while ShK and its analogues that selectively inhibit Kv1.3 channels preferentially suppress the function of chronically-activated effector memory T cells (TEM, TEMRA). Of special interest are the large number of ShK analogues developed at Amgen that suppressed interleukin-2 and interferon gamma production by T cells. This inhibitory effect of Kv1.3 blockers is partial and stimulation strength dependent, with reduced inhibitory efficacy on T cells under strengthened anti-CD3/CD28 stimulation. Chronically-activated CD28null effector memory T cells are implicated in autoimmune diseases (e.g. lupus, Crohn's disease, rheumatoid arthritis, multiple sclerosis). Blockade of Kv1.3 channels in these chronically-activated T cells suppresses calcium signaling, cytokine production (interferon gamma, interleukin-2, interleukin 17), and cell proliferation. Effector memory T cells that are CD28+ are refractory to suppression by Kv1.3 blockers when they are co-stimulated by anti-CD3 and anti-CD28 antibodies, but are sensitive to suppression when stimulated by anti-CD3 antibodies alone. In vivo, ShK-186 paralyzes effector-memory T cells at the site of an inflammatory delayed type hypersensitivity response and prevents these T cells from activating in the inflamed tissue. In contrast, ShK-186 does not affect the homing and motility of naive and TCM cells to and within lymph nodes, most likely because these cells express the KCa3.1 channel and are therefore protected from the effect of Kv1.3 blockade. Effects on microglia Kv1.3 plays an important role in microglial activation. ShK-223, an analogue of ShK-186, decreased lipopolysaccharide (LPS) induced focal adhesion formation by microglia, reversed LPS-induced inhibition of microglial migration, and inhibited LPS-induced upregulation of EH domain containing protein 1 (EHD1), a protein involved in microglia trafficking. Increased Kv1.3 expression was reported in microglia in Alzheimer plaques. Kv1.3 inhibitors may have use in the management of Alzheimer's disease, as reported in a proof-of-concept study in which a small molecule Kv1.3 blocker (PAP-1) alleviated Alzheimer's disease-like characteristics in a mouse model of AD. Efficacy of analogues in animal models of human diseases Experimental autoimmune encephalomyelitis (EAE), a model for multiple sclerosis ShK, ShK-Dap22, ShK-170 and PEGylated ShK-Q16K prevent adoptive-transfer EAE in Lewis rats, a model of multiple sclerosis. Since multiple sclerosis is a relapsing-remitting disease, ShK-186 and ShK-192 were evaluated in a relapsing-remitting EAE model in DA (Dark Agouti) rats. Both prevented and treated disease when administered once a day to once in three days. Thus, Kv1.3 inhibitors are effective in treating disease in rat models of multiple sclerosis when administered alone, and therapeutic effectiveness does not appear to be compromised by compensatory over-expression of KCa3.1 channels. Pristane-induced arthritis (PIA), a model for rheumatoid arthritis ShK-186 was effective in treating PIA when administered every day or on alternate days. A scorpion toxin inhibitor of KV1.3 was also effective in this model. In both these studies, blockade of Kv1.3 alone was sufficient to ameliorate disease and simultaneous blockade of KCa3.1 was not necessary as has been suggested. Rat models of atopic dermatitis Most infiltrating T-cells in skin lesions from patients with moderate-to-severe atopic dermatitis (AD) express high levels of Kv1.3, suggesting that inhibitors of Kv1.3 may be effective in treating AD. Ovalbumin-induced delayed type hypersensitivity and oxazolone-induced dermatitis are considered to be models of atopic dermatitis. ShK, ShK-170, ShK-186, ShK-192 and ShK-IgG-Fc were all effective in the ovalbumin-induced delayed type hypersensitivity model, while a topical formulation of ShK-198 was effective in treating oxazolone-induced dermatitis. Even where compensation by KCa3.1 channels was reported to over-ride KV1.3 block, ShK administered alone suppressed delayed type hypersensitivity significantly in 2 of 3 studies, albeit modestly. Psoriasis
</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.