data_source stringclasses 1
value | prompt listlengths 1 1 | ability stringclasses 6
values | reward_model.ground_truth stringclasses 63
values | reward_model.style stringclasses 1
value | extra_info.answer stringclasses 63
values | extra_info.correct_count int64 0 5 | extra_info.difficulty stringclasses 3
values | extra_info.index int64 1 92k | extra_info.question stringlengths 2.21k 11.1k | extra_info.split stringclasses 1
value | extra_info.cotanswer stringlengths 38 55.3k | reward_model dict | extra_info dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the user Query, starting with \"Belief:... | Product_Substitute_Identification | no | rule | no | 4 | Medium | 75,047 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the user Query, starting with "Belief: customer believes", list... | train |
Let's analyze the user's query and the given product description.
User Query: "nike womens black and white"
Product: "Nike Women's Roshe One Running Shoe, Black/White/Dark Grey, 10"
First, let me understand what I should judge:
1. Is this product a suitable substitute for what the user is asking for?
Now I'll break... | {
"ground_truth": "no",
"style": "rule"
} | {
"answer": "no",
"cotanswer": "\nLet's analyze the user's query and the given product description.\n\nUser Query: \"nike womens black and white\"\nProduct: \"Nike Women's Roshe One Running Shoe, Black/White/Dark Grey, 10\"\n\nFirst, let me understand what I should judge:\n1. Is this product a suitable substitute f... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the user Query, starting with \"Belief:... | Query_Product_Rank | A,B | rule | A,B | 4 | Medium | 82,573 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the user Query, starting with "Belief: customer believes", list... | train |
Okay, let's tackle this problem step by step using the BDI framework. The user's task is to evaluate and sort product titles based on their relevance to the query "memory foam shoes boys".
First, breaking down the query: they're looking for shoes that are both memory foam and intended for boys. So the key factors ar... | {
"ground_truth": "A,B",
"style": "rule"
} | {
"answer": "A,B",
"cotanswer": "\nOkay, let's tackle this problem step by step using the BDI framework. The user's task is to evaluate and sort product titles based on their relevance to the query \"memory foam shoes boys\". \n\nFirst, breaking down the query: they're looking for shoes that are both memory foam an... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the User Review, starting with \"Belief... | Sentiment_Analysis | C: neutral | rule | C: neutral | 3 | Medium | 33,972 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the User Review, starting with "Belief: customer believes", lis... | train |
Let me analyze the user review and create a BDI reasoning process as requested.
First, let's parse the user review:
"Apparently, I bought the wrong model number, but since it was so cheap to buy to start with, I will find someone with that model of bag that I can donate it to. So, no comment on this end!"
This revie... | {
"ground_truth": "C: neutral",
"style": "rule"
} | {
"answer": "C: neutral",
"cotanswer": "\nLet me analyze the user review and create a BDI reasoning process as requested.\n\nFirst, let's parse the user review:\n\"Apparently, I bought the wrong model number, but since it was so cheap to buy to start with, I will find someone with that model of bag that I can donat... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the User Review, starting with \"Belief... | Sentiment_Analysis | B: positive | rule | B: positive | 3 | Medium | 48,186 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the User Review, starting with "Belief: customer believes", lis... | train |
Okay, let's break this down. The user wants me to assess the sentiment of their review using BDI framework. The review says, "I bought this VERY cheap to play sound from my Macbook. It does its job, and I have no complaints." The options are from very positive to very negative.
First, the Beliefs part. The customer b... | {
"ground_truth": "B: positive",
"style": "rule"
} | {
"answer": "B: positive",
"cotanswer": "\nOkay, let's break this down. The user wants me to assess the sentiment of their review using BDI framework. The review says, \"I bought this VERY cheap to play sound from my Macbook. It does its job, and I have no complaints.\" The options are from very positive to very ne... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the User Review, starting with \"Belief... | Sentiment_Analysis | D: negative | rule | D: negative | 3 | Medium | 31,560 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the User Review, starting with "Belief: customer believes", lis... | train |
Okay, let me try to work through this problem step by step. So, the user wants me to assess the sentiment of their given review using the BDI framework and then pick the correct answer from the options provided. The answer is already given as D: negative, but I need to create a logical BDI reasoning process that suppo... | {
"ground_truth": "D: negative",
"style": "rule"
} | {
"answer": "D: negative",
"cotanswer": "\nOkay, let me try to work through this problem step by step. So, the user wants me to assess the sentiment of their given review using the BDI framework and then pick the correct answer from the options provided. The answer is already given as D: negative, but I need to cre... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, r... | Product_Relation_Prediction | B | rule | B | 4 | Medium | 25,524 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively.
For the... | train |
Okay, let's try to figure this out. The user wants to evaluate the titles of Product 1 and Product 2 and choose the correct relation between them. The answer given is B, but I need to use the BDI framework to reason through it without directly referencing the answer.
First, let's break down the product titles. Produc... | {
"ground_truth": "B",
"style": "rule"
} | {
"answer": "B",
"cotanswer": "\nOkay, let's try to figure this out. The user wants to evaluate the titles of Product 1 and Product 2 and choose the correct relation between them. The answer given is B, but I need to use the BDI framework to reason through it without directly referencing the answer.\n\nFirst, let's... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the user Purchase History, starting wit... | Sequential_Recommendation | C | rule | C | 5 | Medium | 56,585 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the user Purchase History, starting with "Belief: customer beli... | train |
Okay, let's tackle this problem step by step using the BDI framework. First, I need to analyze the user's purchase history to determine their beliefs, desires, and intentions.
The user has purchased two items so far. The first is a Thermos travel tumbler, which falls under Home & Kitchen, specifically Thermos. The s... | {
"ground_truth": "C",
"style": "rule"
} | {
"answer": "C",
"cotanswer": "\nOkay, let's tackle this problem step by step using the BDI framework. First, I need to analyze the user's purchase history to determine their beliefs, desires, and intentions. \n\nThe user has purchased two items so far. The first is a Thermos travel tumbler, which falls under Home ... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the user Query, starting with \"Belief:... | Multiclass_Product_Classification | B: The product is somewhat relevant. It fails to fulfill some aspects of the query but the product can be used as a functional substitute. | rule | B: The product is somewhat relevant. It fails to fulfill some aspects of the query but the product can be used as a functional substitute. | 3 | Medium | 72,540 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the user Query, starting with "Belief: customer believes", list... | train |
Let me analyze this query using the Belief-Desire-Intention (BDI) framework along with Reiss's 16 basic desires theory.
First, let's break down the user query and task:
- The task is to evaluate the relevance between the query and product title
- The query is "speck iphone xr case green"
- The product title is "Speck... | {
"ground_truth": "B: The product is somewhat relevant. It fails to fulfill some aspects of the query but the product can be used as a functional substitute.",
"style": "rule"
} | {
"answer": "B: The product is somewhat relevant. It fails to fulfill some aspects of the query but the product can be used as a functional substitute.",
"cotanswer": "\nLet me analyze this query using the Belief-Desire-Intention (BDI) framework along with Reiss's 16 basic desires theory.\n\nFirst, let's break down... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the user Query, starting with \"Belief:... | Product_Substitute_Identification | yes | rule | yes | 3 | Medium | 57,600 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the user Query, starting with "Belief: customer believes", list... | train |
Okay, let's tackle this problem step by step using the BDI framework. The user's query is "ode to happiness" and the product suggested is "Ode To Love: A Journey Of Awakening". I need to determine if the product is a suitable substitute.
First, looking at the Beliefs. The customer believes that "ode to happiness" re... | {
"ground_truth": "yes",
"style": "rule"
} | {
"answer": "yes",
"cotanswer": "\nOkay, let's tackle this problem step by step using the BDI framework. The user's query is \"ode to happiness\" and the product suggested is \"Ode To Love: A Journey Of Awakening\". I need to determine if the product is a suitable substitute. \n\nFirst, looking at the Beliefs. The ... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, r... | Product_Relation_Prediction | A | rule | A | 5 | Medium | 28,145 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. The reasoning process and answer are enclosed within <think> </think> and <answer> </answer> tags, respectively.
For the... | train |
Okay, let's tackle this problem step by step using the BDI framework. First, I need to understand what the user is asking. They want me to evaluate the product titles to assess similarity and if they might be purchased or viewed together, then select the correct option based on the BDI reasoning process.
Starting wit... | {
"ground_truth": "A",
"style": "rule"
} | {
"answer": "A",
"cotanswer": "\nOkay, let's tackle this problem step by step using the BDI framework. First, I need to understand what the user is asking. They want me to evaluate the product titles to assess similarity and if they might be purchased or viewed together, then select the correct option based on the ... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the user Query, starting with \"Belief:... | Query_Product_Rank | B,A | rule | B,A | 5 | Medium | 28,343 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the user Query, starting with "Belief: customer believes", list... | train | Okay, let's tackle this problem using the BDI framework. So, the user wants to rank products A and B based on their relevance to "womens basketball shoes."
First, the Beliefs. The customer believes that the query is about women's basketball shoes specifically. They're likely looking for shoes made for women, not men.... | {
"ground_truth": "B,A",
"style": "rule"
} | {
"answer": "B,A",
"cotanswer": "Okay, let's tackle this problem using the BDI framework. So, the user wants to rank products A and B based on their relevance to \"womens basketball shoes.\" \n\nFirst, the Beliefs. The customer believes that the query is about women's basketball shoes specifically. They're likely l... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the user Query, starting with \"Belief:... | Query_Product_Rank | B,A | rule | B,A | 5 | Medium | 76,660 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the user Query, starting with "Belief: customer believes", list... | train |
Okay, let's tackle this problem step by step using the BDI framework. The user wants to evaluate product titles based on the query "gia tee shirt" and rank them by relevance.
First, the Beliefs. The customer believes that the query terms "gia" and "tee shirt" are important. They expect products matching both terms to... | {
"ground_truth": "B,A",
"style": "rule"
} | {
"answer": "B,A",
"cotanswer": "\nOkay, let's tackle this problem step by step using the BDI framework. The user wants to evaluate product titles based on the query \"gia tee shirt\" and rank them by relevance.\n\nFirst, the Beliefs. The customer believes that the query terms \"gia\" and \"tee shirt\" are importan... |
ECI | [
{
"content": "<s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer. \nThe steps to generate BDI reasoning process:\n(1) Based on the user Purchase History, starting wit... | Sequential_Recommendation | T | rule | T | 3 | Medium | 50,769 | <s>[INST]You are a helpful assistant. The assistant first thinks about the reasoning process in the mind by using Belief-Desire-Intention (BDI) framework and then provides the user with the answer.
The steps to generate BDI reasoning process:
(1) Based on the user Purchase History, starting with "Belief: customer beli... | train |
Let me analyze this situation using the Belief-Desire-Intention (BDI) framework.
First, let me understand the user's purchase history:
1. Video card (XFX AMD Radeon HD 7750)
2. Processor (AMD Phenom II X4)
3. Webcam (HP HD-3110)
4. Keyboard tool (Mechanical Keyboards Inc)
5. Car subwoofers (KICKER)
6. Earbuds (iFrog... | {
"ground_truth": "T",
"style": "rule"
} | {
"answer": "T",
"cotanswer": "\nLet me analyze this situation using the Belief-Desire-Intention (BDI) framework.\n\nFirst, let me understand the user's purchase history:\n\n1. Video card (XFX AMD Radeon HD 7750)\n2. Processor (AMD Phenom II X4)\n3. Webcam (HP HD-3110)\n4. Keyboard tool (Mechanical Keyboards Inc)\n... |
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