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>
antiochienensis (Tsacas, 1964) Engelepogon chrysophora (Tsacas, 1964) Engelepogon collarti (Bequaert, 1964) Engelepogon idiorrhythmicus (Janssens, 1960) Engelepogon keiseri (Tsacas, 1967) Engelepogon nesiotis (Tsacas, 1964) Engelepogon pallida (Theodor, 1980) Engelepogon thasia (Tsacas, 1964) Genus Enigmomorphus Enigmomorphus paradoxus (Hermann, 1912) Genus Epaphroditus Epaphroditus conspicuus (Wulp, 1872) Genus Epiklisis Epiklisis pilitarsis (Becker, 1925) Genus Epipamponeurus Epipamponeurus americanus (Becker, 1919) Genus Erax Erax atticus (Loew, 1871) Erax costalis (Wulp, 1899) Erax crassicauda (Loew, 1862) Erax dilsi (Tomasovic, 2002) Erax ermolenkoi (Lehr, 1992) Erax fuscidus (Pallas, 1818) Erax gracilis (Theodor, 1980) Erax grootaerti (Tomasovic, 2002) Erax hayati (Tomasovic, 2002) Erax macedonicus (Tsacas, 1960) Erax melanothrix (Tsacas, 1960) Erax nigrocinctus (Becker, 1909) Erax nigrosetosus (Theodor, 1980) Erax nubeculus (Loew, 1848) Erax rjabovi (Richter, 1963) Erax sedulus (Richter, 1963) Erax tenuicornis (Loew, 1848) Genus Eraxasilus Eraxasilus acuminatus (Carrera, 1959) Eraxasilus gerion (Walker, 1849) Eraxasilus hebes (Walker, 1855) Eraxasilus longiusculus (Walker, 1855) Eraxasilus peticus (Walker, 1849) Eraxasilus potamon (Walker, 1851) Eraxasilus pruinosus (Carrera, 1959) Genus Erebunus Erebunus badghysicus (Lehr, 1987) Erebunus mirabilis (Richter, 1966) Genus Eremisca Eremisca autumnalis (Zinovjeva, 1956) Eremisca gobia (Lehr, 1972) Eremisca interposita (Lehr, 1987) Eremisca laticerca (Lehr, 1987) Eremisca major (Lehr, 1964) Eremisca multis (Lehr, 1987) Eremisca obscura (Lehr, 1987) Eremisca orientalis (Lehr, 1972) Eremisca poecilus (Becker, 1923) Eremisca stackelbergi (Lehr, 1964) Eremisca subarenosa (Lehr, 1987) Eremisca trivialis (Lehr, 1987) Eremisca vernalis (Zinovjeva, 1956) Genus Eremodromus Eremodromus flaviventris (Efflatoun, 1937) Eremodromus gracilis (Paramonov, 1930) Eremodromus noctivagus (Zimin, 1928) Eremodromus zimini (Lehr, 1979) Genus Eremonotus Eremonotus nudus (Theodor, 1980) Genus Eriopogon Eriopogon jubatus (Becker, 1906) Eriopogon spatenkai (Hradský & Hüttinger, 1995) Genus Erythropogon Erythropogon ichneumoniformis (White, 1914) Genus Esatanas Esatanas chan (Engel, 1934) Esatanas kozlovi (Lehr, 1986) Esatanas shah (Róndani, 1873) Esatanas velox (Lehr, 1963) Esatanas villosus (Lehr, 1986) Genus Eucyrtopogon Eucyrtopogon albibarbus (Curran, 1923) Eucyrtopogon calcaratus (Curran, 1923) Eucyrtopogon comantis (Curran, 1923) Eucyrtopogon diversipilosis (Curran, 1923) Eucyrtopogon incompletus (Adisoemarto, 1967) Eucyrtopogon kelloggi (Wilcox, 1936) Eucyrtopogon maculosus (Coquillett, 1904) Eucyrtopogon nebulo (Osten-Sacken, 1877) Eucyrtopogon nigripes (Jones, 1907) Eucyrtopogon punctipennis (Melander, 1923) Eucyrtopogon varipennis (Coquillett, 1904) Genus Eudioctria Eudioctria beameri (Wilcox & Martin, 1941) Eudioctria brevis (Banks, 1917) Eudioctria disjuncta (Adisoemarto & Wood, 1975) Eudioctria dissimilis (Adisoemarto & Wood, 1975) Eudioctria doanei (Melander, 1924) Eudioctria media (Banks, 1917) Eudioctria monrovia (Wilcox & Martin, 1941) Eudioctria nitida (Williston, 1883) Eudioctria propinqua (Bromley, 1924) Eudioctria unica (Adisoemarto & Wood, 1975) Genus Eumecosoma Eumecosoma ayala (Kaletta, 1974) Eumecosoma caerulum (Scarbrough & Perez-Gelabert, 2006) Eumecosoma calverti (Hine, 1917) Eumecosoma carmina (Kaletta, 1974) Eumecosoma dicromum (Bigot, 1878) Eumecosoma hirsutum (Hermann, 1912) Eumecosoma metallescens (Schiner, 1868) Eumecosoma pleuritica (Wiedemann, 1828) Eumecosoma shropshirei (Curran, 1930) Eumecosoma staurophorum (Schiner, 1868) Eumecosoma tiarensis (Kaletta, 1978) Genus Eurhabdus Eurhabdus jamaicensis (Farr, 1973) Eurhabdus longissimus (Tomasovic, 2002) Eurhabdus sororius (Scarbrough & Perez-Gelabert, ) Eurhabdus zephyreus (Aldrich, 1923) Genus Euscelidia Euscelidia abbreviata Dikow, 2003 Euscelidia acuminata Dikow, 2003 Euscelidia adusta Dikow, 2003 Euscelidia anthrax (Janssens, 1957) Euscelidia atrata Dikow, 2003 Euscelidia bechuana Dikow, 2003 Euscelidia bequaerti (Janssens, 1957) Euscelidia bicolor (Janssens, 1954) Euscelidia bishariensis (Efflatoun, 1937) Euscelidia cacula Dikow, 2003 Euscelidia cana Dikow, 2003 Euscelidia capensis Dikow, 2003 Euscelidia castanea (Janssens, 1954) Euscelidia cobice Dikow, 2003 Euscelidia crena Dikow, 2003 Euscelidia discors (Speiser, 1913) Euscelidia dorata (Oldroyd, 1970) Euscelidia erichthenii Dikow, 2003 Euscelidia fastigium (Martin, 1964) Euscelidia festiva (Janssens, 1954) Euscelidia fistula Dikow, 2003 Euscelidia flava Dikow, 2003 Euscelidia glabra Dikow, 2003 Euscelidia gutianensis (Shi, 1995) Euscelidia hesperia Dikow, 2003 Euscelidia hyalina Dikow, 2003 Euscelidia insolita Dikow, 2003 Euscelidia kasungu Dikow, 2003 Euscelidia lata Dikow, 2003 Euscelidia lepida Dikow, 2003 Euscelidia livida Dikow, 2003 Euscelidia longibifida Dikow, 2003 Euscelidia lucida (Oldroyd, 1939) Euscelidia lucioides Dikow, 2003 Euscelidia milva Dikow, 2003 Euscelidia moyoensis (Oldroyd, 1970) Euscelidia mucronata Dikow, 2003 Euscelidia
</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.