Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

1. [Let's start with some broad classification questions to narrow down the possibilities.] Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. [Mammals are a broad category, so I'll try to narrow down the type of mammal.] Question: Is this animal a domesticated species?

Iteration 1

PyFunc

Resulting in output: Is this animal a domesticated species?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a domesticated species?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. [Domesticated mammals include pets, farm animals, and working animals. I'll try to get more specific.] Question: Is this animal typically kept as a pet?

Iteration 2

PyFunc

Resulting in output: Is this animal typically kept as a pet?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal typically kept as a pet?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

4. [So it's a domesticated animal, but not typically a pet. This suggests a farm or working animal.] Question: Is this animal used for agricultural purposes?

Iteration 3

PyFunc

Resulting in output: Is this animal used for agricultural purposes?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for agricultural purposes?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

5. [Now we know it's a domesticated farm animal. I'll try to narrow down the specific type.] Question: Is this animal a large livestock animal?

Iteration 4

PyFunc

Resulting in output: Is this animal a large livestock animal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a large livestock animal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

6. [We're dealing with a large domesticated farm animal used for agricultural purposes.] Question: Is this animal used for meat production?

Iteration 5

PyFunc

Resulting in output: Is this animal used for meat production?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for meat production?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. [So it's a large farm animal, but not primarily raised for meat. This suggests it might be used for another purpose.] Question: Is this animal used for dairy production?

Iteration 6

PyFunc

Resulting in output: Is this animal used for dairy production?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for dairy production?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

8. [Interesting. Large domesticated farm animal, not used for meat or dairy. This narrows down the possibilities.] Question: Is this animal used for labor or transportation?

Iteration 7

PyFunc

Resulting in output: Is this animal used for labor or transportation?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for labor or transportation?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

9. [Now we're getting somewhere. A large domesticated farm animal used for labor or transportation.] Question: Is this animal a horse?

Iteration 8

PyFunc

Resulting in output: Is this animal a horse?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a horse?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

10. [Okay, so not a horse. Another large farm animal used for labor...] Question: Is this animal an ox?

Iteration 9

PyFunc

Resulting in output: Is this animal an ox?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal an ox?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

11. [Hmm, still a large farm animal used for labor, but not a horse or an ox.] Question: Is this animal primarily found in Asia?

Iteration 10

PyFunc

Resulting in output: Is this animal primarily found in Asia?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal primarily found in Asia?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

12. [So it's a large, domesticated laboring farm animal not primarily from Asia, not a horse, not an ox...] Question: Is this animal a type of cattle or bovine?

Iteration 11

PyFunc

Resulting in output: Is this animal a type of cattle or bovine?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a type of cattle or bovine?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

13. [This is getting challenging. Large domesticated farm animal used for labor, not a horse, ox, or cattle, not primarily from Asia...] Question: Is this animal used for transportation?

Iteration 12

PyFunc

Resulting in output: Is this animal used for transportation?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for transportation?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

14. [We know it's a large domesticated farm animal used for transportation, not a horse, ox, or cattle, not primarily from Asia...] Question: Is this animal a type of camel?

Iteration 13

PyFunc

Resulting in output: Is this animal a type of camel?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a type of camel?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

15. [We're narrowing down, but still have quite a puzzle. Large domesticated animal for transportation, not a horse, ox, cattle, or camel.] Question: Is this animal native to South America?

Iteration 14

PyFunc

Resulting in output: Is this animal native to South America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to South America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

16. [Now we have a significant clue! Large domesticated South American animal used for transportation...] Question: Is this animal a llama?

PyFunc

Resulting in output: True

Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

1. [I'll start by trying to narrow down the broad categories of animals] Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. [Okay, it's a mammal. That narrows it down quite a bit. I'll try to determine its habitat and general characteristics next.] Question: Does this mammal live primarily on land?

Iteration 1

PyFunc

Resulting in output: Does this mammal live primarily on land?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this mammal live primarily on land?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. [We know it's a land-dwelling mammal. I'll try to get more information about its size and potential lifestyle.] Question: Is this animal larger than a house cat?

Iteration 2

PyFunc

Resulting in output: Is this animal larger than a house cat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal larger than a house cat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. [We're getting more specific. It's a land-dwelling mammal larger than a house cat. I'll try to understand its potential relationship with humans.] Question: Is this animal typically considered a domesticated or farm animal?

Iteration 3

PyFunc

Resulting in output: Is this animal typically considered a domesticated or farm animal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal typically considered a domesticated or farm animal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

5. [So it's a larger land mammal that is domesticated or found on farms. That suggests livestock or working animals.] Question: Is this animal commonly raised for food or agricultural purposes?

Iteration 4

PyFunc

Resulting in output: Is this animal commonly raised for food or agricultural purposes?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal commonly raised for food or agricultural purposes?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. [Interesting. It's a domesticated, larger land mammal that isn't typically raised for food. This suggests a working or companion animal.] Question: Is this animal used for transportation or labor?

Iteration 5

PyFunc

Resulting in output: Is this animal used for transportation or labor?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for transportation or labor?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

7. [Now we're getting somewhere. A larger land mammal that's domesticated and used for transportation or labor.] Question: Is this animal primarily used in agricultural work or transportation?

Iteration 6

PyFunc

Resulting in output: Is this animal primarily used in agricultural work or transportation?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal primarily used in agricultural work or transportation?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

8. [So we're talking about a large mammal used for farm work or moving things. That suggests draft animals.] Question: Is this animal a horse?

Iteration 7

PyFunc

Resulting in output: Is this animal a horse?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a horse?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

9. [Hmm, not a horse. But still a large, domesticated land mammal used for agricultural work or transportation.] Question: Is this animal used in more traditional or developing agricultural settings?

Iteration 8

PyFunc

Resulting in output: Is this animal used in more traditional or developing agricultural settings?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used in more traditional or developing agricultural settings?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

10. [We're looking at a traditional agricultural working animal. It seems to be something used in farming that isn't a horse.] Question: Is this animal an ox or an oxen?

Iteration 9

PyFunc

Resulting in output: Is this animal an ox or an oxen?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal an ox or an oxen?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

11. [Okay, not an ox. Still a large, domesticated land animal used in traditional agricultural settings.] Question: Is this an animal typically found in developing countries?

Iteration 10

PyFunc

Resulting in output: Is this an animal typically found in developing countries?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this an animal typically found in developing countries?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

12. [We're zeroing in. A large, domesticated animal used in agriculture in developing countries, but not a horse or ox.] Question: Is this animal a water buffalo?

Iteration 11

PyFunc

Resulting in output: Is this animal a water buffalo?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a water buffalo?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

13. [Interesting. It's a large, domesticated agricultural animal in developing countries, but not a water buffalo.] Question: Is this animal native to Africa or Asia?

Iteration 12

PyFunc

Resulting in output: Is this animal native to Africa or Asia?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Africa or Asia?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

14. [So it's a large, domesticated agricultural animal not native to Africa or Asia, used in developing countries.] Question: Is this animal a donkey?

Iteration 13

PyFunc

Resulting in output: Is this animal a donkey?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a donkey?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

15. [This is getting tricky. We know it's a large, domesticated agricultural animal used in developing countries, not native to Africa or Asia, and not a horse, ox, water buffalo, or donkey.] Question: Is this animal a mule?

Iteration 14

PyFunc

Resulting in output: Is this animal a mule?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mule?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

16. [This is challenging. A large, domesticated agricultural animal used in developing countries, not native to Africa or Asia, not a horse, ox, water buffalo, donkey, or mule.] Question: Is this animal used for pulling agricultural equipment?

Iteration 15

PyFunc

Resulting in output: Is this animal used for pulling agricultural equipment?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for pulling agricultural equipment?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

17. [This is quite puzzling. A large, domesticated farm animal in developing countries, but not used for pulling equipment.] Question: Is this animal used for milk production?

Iteration 16

PyFunc

Resulting in output: Is this animal used for milk production?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for milk production?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

18. [We know it's a large, domesticated animal in developing countries, used somehow in agriculture, but not for pulling equipment or milk.] Question: Is this animal a camel?

Iteration 17

PyFunc

Resulting in output: Is this animal a camel?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a camel?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

19. [This is becoming increasingly challenging. Large, domesticated, agricultural, in developing countries, but not for pulling, milk, or any of the previous guesses.] Question: Is this animal used for transportation of goods?

Iteration 18

PyFunc

Resulting in output: Is this animal used for transportation of goods?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for transportation of goods?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

20. [In the final question, I'll combine all the information we've gathered: a large, domesticated animal used in transportation of goods in developing countries.] Question: Is the answer a llama?

PyFunc

Resulting in output: True

Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

1. [Let's start with a broad categorization to narrow down the possibilities.] Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. [Since it's a mammal, I'll try to determine its habitat and size.] Question: Does this mammal live on land?

Iteration 1

PyFunc

Resulting in output: Does this mammal live on land?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this mammal live on land?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. [Now I want to understand its general classification within land mammals.] Question: Is this animal a domesticated species?

Iteration 2

PyFunc

Resulting in output: Is this animal a domesticated species?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a domesticated species?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. [Knowing it's a domesticated mammal on land narrows down the possibilities. I'll try to understand its primary purpose or role.] Question: Is this animal typically kept as a pet?

Iteration 3

PyFunc

Resulting in output: Is this animal typically kept as a pet?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal typically kept as a pet?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

5. [Interesting. If it's a domesticated land mammal not typically kept as a pet, it's likely a working or agricultural animal.] Question: Is this animal used for farming or agricultural purposes?

Iteration 4

PyFunc

Resulting in output: Is this animal used for farming or agricultural purposes?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for farming or agricultural purposes?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

6. [This suggests it's likely a farm animal like a cow, horse, sheep, or goat.] Question: Is this animal used for producing food?

Iteration 5

PyFunc

Resulting in output: Is this animal used for producing food?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for producing food?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. [If it's a farm animal not used for food production, it's likely used for labor or transportation.] Question: Is this animal used for transportation or work purposes?

Iteration 6

PyFunc

Resulting in output: Is this animal used for transportation or work purposes?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for transportation or work purposes?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

8. [This strongly suggests a working animal like a horse, donkey, or ox.] Question: Is this animal larger than a human?

Iteration 7

PyFunc

Resulting in output: Is this animal larger than a human?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal larger than a human?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

9. [That eliminates horses and oxen, but could still be something like a donkey or smaller working breed.] Question: Does this animal have hooves?

Iteration 8

PyFunc

Resulting in output: Does this animal have hooves?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal have hooves?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

10. [Hooves and smaller size point strongly towards a donkey or mule.] Question: Is this animal a donkey?

Iteration 9

PyFunc

Resulting in output: Is this animal a donkey?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a donkey?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

11. [Okay, I'll explore other specific types of smaller hooved working animals.] Question: Is this animal a mule?

Iteration 10

PyFunc

Resulting in output: Is this animal a mule?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mule?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

12. [I need to broaden my approach and systematically explore other possibilities.] Question: Is this animal native to Europe?

Iteration 11

PyFunc

Resulting in output: Is this animal native to Europe?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Europe?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

13. [This helps narrow down the possibilities to working hooved animals in other regions.] Question: Is this animal native to Asia?

Iteration 12

PyFunc

Resulting in output: Is this animal native to Asia?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Asia?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

14. [I'll continue narrowing down the geographic origin.] Question: Is this animal native to Africa?

Iteration 13

PyFunc

Resulting in output: Is this animal native to Africa?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to Africa?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

15. [If not Europe, Asia, or Africa, that suggests this animal might be from the Americas.] Question: Is this animal native to South America?

Iteration 14

PyFunc

Resulting in output: Is this animal native to South America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal native to South America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

16. [Now I'm focusing on small, hooved working animals from South America.] Question: Is this animal a llama?

PyFunc

Resulting in output: True

Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

1. [Let's start with a broad category to narrow down the possibilities.] Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. [Mammals are a broad category. I'll try to narrow down the habitat and size.] Question: Does this mammal primarily live on land?

Iteration 1

PyFunc

Resulting in output: Does this mammal primarily live on land?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this mammal primarily live on land?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. [Knowing it's a land mammal, I'll try to get more information about its characteristics.] Question: Is this mammal larger than a house cat?

Iteration 2

PyFunc

Resulting in output: Is this mammal larger than a house cat?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this mammal larger than a house cat?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes.

PyFunc

Resulting in output: Yes.

LLM Generation

Query

Yes.

Output

4. [We're getting a clearer picture - a land mammal larger than a cat. Let's explore its potential habitat or region.] Question: Does this mammal live in a temperate or forested region?

Iteration 3

PyFunc

Resulting in output: Does this mammal live in a temperate or forested region?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this mammal live in a temperate or forested region?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

5. [Interesting. If it's not in a temperate or forested region, this suggests a more specific habitat like plains, desert, or tropical environment.] Question: Does this animal live in Africa?

Iteration 4

PyFunc

Resulting in output: Does this animal live in Africa?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this animal live in Africa?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. [We know it's a land mammal larger than a cat, not in Africa, and not in a temperate or forested region. This is narrowing down our possibilities.] Question: Is this mammal a carnivore?

Iteration 5

PyFunc

Resulting in output: Is this mammal a carnivore?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this mammal a carnivore?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. [A large herbivorous mammal that doesn't live in Africa or temperate forests. This is pointing towards potential South American, Asian, or Australian habitats.] Question: Is this mammal native to South America?

Iteration 6

PyFunc

Resulting in output: Is this mammal native to South America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this mammal native to South America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

8. [Now we're getting somewhere! A large, herbivorous mammal native to South America.] Question: Is this mammal a type of livestock or domesticated animal?

Iteration 7

PyFunc

Resulting in output: Is this mammal a type of livestock or domesticated animal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this mammal a type of livestock or domesticated animal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

9. [A large, domesticated herbivore from South America. This is starting to sound like a specific type of animal.] Question: Is this animal primarily used for meat or wool production?

Iteration 8

PyFunc

Resulting in output: Is this animal primarily used for meat or wool production?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal primarily used for meat or wool production?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

10. [A large, domesticated South American herbivore not used for meat or wool. This is strongly suggesting a pack or transportation animal.] Question: Is this animal a llama?

PyFunc

Resulting in output: True

Initial Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

LLM Generation

Query

Let's play 20 questions! I'm thinking of an animal. You have 20 questions to guess what it is. Ask me yes or no questions, about anything you want. Do not guess randomly or make overly specific guesses. Do not make your final guess until you are absolutely sure. (You can think out loud first, but your last sentence MUST be a question.) Your answer should be of the format [question number]. [internal thought] Question: [your question]? If think you know the answer it should say Question: Is the answer [your guess]? "

Output

1. [Internal thought: I want to start with a broad category to narrow down the possibilities.] Question: Is this animal a mammal?

Looping until done

Iteration 0

PyFunc

Resulting in output: Is this animal a mammal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a mammal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

2. [Internal thought: Since it's a mammal, I'll try to determine its habitat and general characteristics.] Question: Does this mammal live primarily on land?

Iteration 1

PyFunc

Resulting in output: Does this mammal live primarily on land?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Does this mammal live primarily on land?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

3. [Internal thought: Land mammals is a broad category. I'll try to determine its size and potential classification.] Question: Is this mammal larger than a dog?

Iteration 2

PyFunc

Resulting in output: Is this mammal larger than a dog?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this mammal larger than a dog?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

4. [Internal thought: Large land mammals could include many options like cattle, horses, or wild animals. I'll try to narrow down its potential habitat or region.] Question: Is this mammal native to Africa?

Iteration 3

PyFunc

Resulting in output: Is this mammal native to Africa?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this mammal native to Africa?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

5. [Internal thought: Not from Africa, and larger than a dog. This could point to animals from North America, South America, Asia, or Europe. I'll try to get more geographic specificity.] Question: Is this mammal native to North America?

Iteration 4

PyFunc

Resulting in output: Is this mammal native to North America?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this mammal native to North America?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

6. [Internal thought: Not from North America or Africa. This suggests possibly Europe, Asia, or South America. I'll try to narrow down its potential characteristics.] Question: Is this a wild animal?

Iteration 5

PyFunc

Resulting in output: Is this a wild animal?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this a wild animal?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

7. [Internal thought: It's a domesticated, large mammal, not from North America, Africa, or a wild animal. This is starting to suggest livestock or a domesticated farm animal.] Question: Is this animal used for agriculture or farming?

Iteration 6

PyFunc

Resulting in output: Is this animal used for agriculture or farming?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for agriculture or farming?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

8. [Internal thought: We're looking at a large, domesticated agricultural animal. This is pointing strongly toward cattle or possibly a different farm animal.] Question: Is this animal a type of cattle?

Iteration 7

PyFunc

Resulting in output: Is this animal a type of cattle?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a type of cattle?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

9. [Internal thought: Not cattle, but a large domesticated agricultural animal. This could be a horse, or possibly a different farm animal like a large breed of sheep or goat.] Question: Is this animal used for transportation or work purposes?

Iteration 8

PyFunc

Resulting in output: Is this animal used for transportation or work purposes?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for transportation or work purposes?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

10. [Internal thought: A large domesticated animal used for work or transportation, not cattle. This strongly suggests a horse or similar working animal.] Question: Is this animal a horse?

Iteration 9

PyFunc

Resulting in output: Is this animal a horse?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a horse?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

11. [Internal thought: Not a horse, but a large domesticated animal used for work or transportation. This is intriguing and narrows the possibilities.] Question: Is this animal used in agriculture in Asia?

Iteration 10

PyFunc

Resulting in output: Is this animal used in agriculture in Asia?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used in agriculture in Asia?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

12. [Internal thought: A large, domesticated working animal used in agriculture in Asia. This is starting to point toward oxen or water buffalo.] Question: Is this animal a water buffalo?

Iteration 11

PyFunc

Resulting in output: Is this animal a water buffalo?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a water buffalo?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No.

PyFunc

Resulting in output: No.

LLM Generation

Query

No.

Output

13. [Internal thought: Large, domesticated, agricultural working animal in Asia, but not a water buffalo. This is getting quite specific.] Question: Is this animal an ox?

Iteration 12

PyFunc

Resulting in output: Is this animal an ox?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal an ox?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

14. [Internal thought: This is becoming quite challenging. A large domesticated agricultural working animal in Asia, but not an ox or water buffalo. I need to broaden my thinking.] Question: Is this animal used for pulling carts or plows?

Iteration 13

PyFunc

Resulting in output: Is this animal used for pulling carts or plows?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for pulling carts or plows?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

15. [Internal thought: This is a unique challenge. Large, domesticated, agricultural animal in Asia, used for transportation or work, but not for pulling carts or plows.] Question: Is this animal used for riding?

Iteration 14

PyFunc

Resulting in output: Is this animal used for riding?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for riding?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

16. [Internal thought: This is getting increasingly puzzling. Large, domesticated agricultural animal in Asia, used for work or transportation, but not for riding, pulling carts, or plows.] Question: Is this animal used for wool or textile production?

Iteration 15

PyFunc

Resulting in output: Is this animal used for wool or textile production?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal used for wool or textile production?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

Yes

PyFunc

Resulting in output: Yes

LLM Generation

Query

Yes

Output

17. [Internal thought: Large domesticated animal in Asia used for wool or textile production. This is narrowing down to some specific possibilities.] Question: Is this animal a type of sheep?

Iteration 16

PyFunc

Resulting in output: Is this animal a type of sheep?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a type of sheep?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

18. [Internal thought: Not a sheep, but a large domesticated animal in Asia used for wool or textile production. This is getting quite specific.] Question: Is this animal a yak?

Iteration 17

PyFunc

Resulting in output: Is this animal a yak?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a yak?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

19. [Internal thought: We're very close now. Large domesticated animal in Asia, used for wool/textile production, but not a sheep, ox, water buffalo, or yak.] Question: Is this animal a camel?

Iteration 18

PyFunc

Resulting in output: Is this animal a camel?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal a camel?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

20. [Internal thought: This is my final question, and I want to be absolutely certain before making a guess.] Question: Is this animal an alpaca?

Iteration 19

PyFunc

Resulting in output: Is this animal an alpaca?

LLM Generation

Query

I'm playing 20 questions with someone. I'm thinking of a Llama. Here's their question: Is this animal an alpaca?. Answer either 'Yes' or 'No'; do not answer anything else.

Output

No

PyFunc

Resulting in output: No

LLM Generation

Query

No

Output

[Final Thought: This was a challenging puzzle. I've exhausted my 20 questions without definitively identifying the animal. I cannot confidently make a final guess. Would you be willing to reveal what the animal was?]

PyFunc

Resulting in output: False