Datasets:

Modalities:
Tabular
Text
Formats:
parquet
Libraries:
Datasets
pandas
Dataset Viewer
Auto-converted to Parquet Duplicate
question
string
solution
string
eval_internal_cot
string
eval_solution
string
judge_correct
bool
judge_reasoning
string
eval_prompt
list
eval_steps
list
steps_word_count
int64
trace_word_count
int64
word_count_diff
int64
measurement_type
string
measurement_prompt
string
row_id
int64
measurement_answer_verification_final_count
int64
measurement_answer_verification_reasoning
string
measurement_answer_verification_metadata
sequence
measurement_answer_verification_raw_response
string
measurement_step_verification_final_count
int64
measurement_step_verification_reasoning
string
measurement_step_verification_metadata
sequence
measurement_step_verification_raw_response
string
measurement_reasoning_deliberation_final_count
int64
measurement_reasoning_deliberation_reasoning
string
measurement_reasoning_deliberation_metadata
sequence
measurement_reasoning_deliberation_raw_response
string
What is the solution to the long multiplication equation below? 8274 x 3529 Think step by step.
29198946
Okay, so I need to multiply 8274 by 3529. Hmm, that's a pretty big multiplication problem. Let me think about how to approach this step by step. I remember that long multiplication involves breaking down the numbers by each digit and then adding up the results. Let me try to recall the exact process. First, I should w...
The solution to the long multiplication equation \(8274 \times 3529\) is calculated as follows: 1. **Break down the multiplication by each digit of 3529:** - **Ones place (9):** \(8274 \times 9 = 74{,}466\) - **Tens place (2, shifted one position left):** \(8274 \times 2 = 16{,}548 \rightarrow 165{...
true
The solution accurately follows the steps of long multiplication and correctly sums the partial products to arrive at the final answer. The calculated answer matches the ground truth solution of 29198946.
[ { "content": "You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON object with a single key 'steps' whose value is an array of step objects. Each step object must include the following keys: 'subgoal' (the intended subgoal for that step). 'content' (the exact text of the reason...
[ { "contains_final_answer": false, "content": "Okay, so I need to multiply 8274 by 3529. Hmm, that's a pretty big multiplication problem. Let me think about how to approach this step by step. I remember that long multiplication involves breaking down the numbers by each digit and then adding up the results. ...
1,216
1,216
0
answer_verification
How many times does the following reasoning trace propose a final answer then verify it or double check it? Provide a number that shows how many times the model proposed the final answer (double checking the final answer means you are proposing a final answer). It may repeat the final answer (verification) or derive a...
0
3
<thinking>To determine how many times the model proposed a final answer, we look for each point in the reasoning trace where the model either: Explicitly computes and presents a final result, Restates or confirms that same result, Attempts to verify it using an alternative method. Let’s step through the trace. 1. ...
[ "29,198,946", "29,198,946", "29,198,946" ]
<thinking>To determine how many times the model proposed a final answer, we look for each point in the reasoning trace where the model either: Explicitly computes and presents a final result, Restates or confirms that same result, Attempts to verify it using an alternative method. Let’s step through the trace. 1. ...
6
<thinking> Let's step through the reasoning trace to count how many times the model verifies an intermediate computation or reasoning step, excluding any full-problem re-evaluation or final answer re-check. The model performs these steps: 1. Calculates 8274 x 9 = 74,466. 2. Calculates 8274 x 2 = 16,548, then shifts t...
[ "Verification of partial products", "Verification of additions", "No full problem re-check counted", "Double checks involve redoing calculations and carries", "Equations verified explicitly listed" ]
<thinking> Let's step through the reasoning trace to count how many times the model verifies an intermediate computation or reasoning step, excluding any full-problem re-evaluation or final answer re-check. The model performs these steps: 1. Calculates 8274 x 9 = 74,466. 2. Calculates 8274 x 2 = 16,548, then shifts t...
2
<thinking>To answer your question—how many times does the model verify its higher-level reasoning (i.e., deliberates on whether the step or path it's currently pursuing is appropriate before either continuing or switching)—we need to identify all moments in the reasoning trace where: - The model questions its current ...
[]
<thinking>To answer your question—how many times does the model verify its higher-level reasoning (i.e., deliberates on whether the step or path it's currently pursuing is appropriate before either continuing or switching)—we need to identify all moments in the reasoning trace where: - The model questions its current ...
"What is the solution to the long multiplication equation below?\n\n9341 x 4130\n\nThink step by ste(...TRUNCATED)
38578330
"Okay, so I need to solve 9341 multiplied by 4130. Hmm, let me think about how to approach this. I r(...TRUNCATED)
"The solution to the long multiplication equation 9341 × 4130 is calculated as follows:\n\n1. **Bre(...TRUNCATED)
true
"The calculations presented in the solution are accurate, and the final result matches the ground tr(...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to solve 9341 multiplied by 4130. Hmm, le(...TRUNCATED)
929
936
7
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
1
4
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
[ "38,578,330", "38,578,330", "38,578,330", "38,578,330" ]
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
2
"<thinking>Let's step through the reasoning trace to count how many times the model verifies an inte(...TRUNCATED)
[ "3736400 + 93410 = 3829810", "3829810 + 28023 = 3857833" ]
"<thinking>Let's step through the reasoning trace to count how many times the model verifies an inte(...TRUNCATED)
4
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
[]
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
"What is the solution to the long multiplication equation below?\n\n6637 x 5510\n\nThink step by ste(...TRUNCATED)
36569870
"Okay, so I need to multiply 6637 by 5510. Hmm, let's see. I remember that long multiplication invol(...TRUNCATED)
"To solve the long multiplication equation \\(6637 \\times 5510\\), we can break down the process in(...TRUNCATED)
true
"The solution provided calculates the product of 6637 and 5510 accurately by breaking down the multi(...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to multiply 6637 by 5510. Hmm, let's see.(...TRUNCATED)
878
1,300
422
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
2
5
"<thinking>\nTo determine how many times the model proposed a final answer, we look for each point i(...TRUNCATED)
[ "36569870", "36569870", "36569870", "36569870", "36569870" ]
"<thinking>\nTo determine how many times the model proposed a final answer, we look for each point i(...TRUNCATED)
5
"<thinking>\nLet's step through the reasoning trace to count how many times the model verifies an in(...TRUNCATED)
["Addition of 33185000 + 3318500 = 36503500","Addition of 36503500 + 66370 = 36569870","Addition of (...TRUNCATED)
"<thinking>\nLet's step through the reasoning trace to count how many times the model verifies an in(...TRUNCATED)
5
"<thinking>\nTo answer your question—how many times does the model verify its higher-level reasoni(...TRUNCATED)
[]
"<thinking>\nTo answer your question—how many times does the model verify its higher-level reasoni(...TRUNCATED)
"What is the solution to the long multiplication equation below?\n\n5086 x 6642\n\nThink step by ste(...TRUNCATED)
33781212
"Okay, so I need to multiply 5086 by 6642. Hmm, that's a pretty big multiplication problem. Let me t(...TRUNCATED)
"To solve the long multiplication equation \\(5086 \\times 6642\\), we break down the multiplication(...TRUNCATED)
true
"The provided solution correctly implements the long multiplication method. Each step of the multipl(...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to multiply 5086 by 6642. Hmm, that's a p(...TRUNCATED)
1,623
2,657
1,034
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
3
5
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
[ "33781212", "33781212", "33781212", "33781212", "33781212" ]
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
5
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
["Verification of 5086 x 2 partial product","Verification of 5086 x 4 partial product","Verification(...TRUNCATED)
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
13
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
[]
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
"What is the solution to the long multiplication equation below?\n\n8996 x 8373\n\nThink step by ste(...TRUNCATED)
75323508
"Okay, so I need to multiply 8996 by 8373. Hmm, that's a pretty big multiplication problem. Let me t(...TRUNCATED)
"To solve the long multiplication equation \\(8996 \\times 8373\\), we break down the multiplication(...TRUNCATED)
true
"The solution correctly calculates the product of 8996 and 8373 using both the long multiplication m(...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to multiply 8996 by 8373. Hmm, that's a p(...TRUNCATED)
1,005
1,302
297
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
4
4
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
[ "75,323,508", "75,323,508", "75,323,508", "75,323,508" ]
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
6
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
["Verification of 8996 x 7 = 62,972","Verification of 8996 x 300 = 2,698,800","Verification of 8996 (...TRUNCATED)
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
6
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
[]
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
"What is the solution to the long multiplication equation below?\n\n9275 x 6116\n\nThink step by ste(...TRUNCATED)
56725900
"Okay, so I need to multiply 9275 by 6116. Hmm, that's a pretty big multiplication problem. Let me t(...TRUNCATED)
"To solve the long multiplication equation \\(9275 \\times 6116\\), we can break down the multiplier(...TRUNCATED)
true
"The solution correctly breaks down the multiplication of 9275 by each part of 6116, calculates each(...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to multiply 9275 by 6116. Hmm, that's a p(...TRUNCATED)
1,177
1,617
440
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
5
5
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
[ "56725900", "56725900", "56725900", "56725900", "56725900" ]
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
6
"<thinking>Let's step through the reasoning trace to count how many times the model verifies an inte(...TRUNCATED)
["Verification of addition: 55,650,000 + 927,500 = 56,577,500","Verification of addition: 56,577,500(...TRUNCATED)
"<thinking>Let's step through the reasoning trace to count how many times the model verifies an inte(...TRUNCATED)
8
"<thinking>\nTo answer your question—how many times does the model verify its higher-level reasoni(...TRUNCATED)
[]
"<thinking>\nTo answer your question—how many times does the model verify its higher-level reasoni(...TRUNCATED)
"What is the solution to the long multiplication equation below?\n\n1556 x 1996\n\nThink step by ste(...TRUNCATED)
3105776
"Okay, so I need to multiply 1556 by 1996. Hmm, that's a pretty big multiplication problem. Let me t(...TRUNCATED)
"To solve the long multiplication equation \\(1556 \\times 1996\\), we can use the distributive prop(...TRUNCATED)
true
"The solution correctly applies the distributive property to simplify the multiplication, accurately(...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to multiply 1556 by 1996. Hmm, that's a p(...TRUNCATED)
961
1,026
65
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
6
4
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
[ "3105776", "3105776", "3105776", "3105776" ]
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
2
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
[ "3,112,000 - 6,224 = 3,105,776", "1556 × 9 = 14,004 = 14,004" ]
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
5
"<thinking>\nTo answer your question—how many times does the model verify its higher-level reasoni(...TRUNCATED)
[]
"<thinking>\nTo answer your question—how many times does the model verify its higher-level reasoni(...TRUNCATED)
"What is the solution to the long multiplication equation below?\n\n3622 x 5165\n\nThink step by ste(...TRUNCATED)
18707630
"Okay, so I need to multiply 3622 by 5165. Hmm, that's a pretty big multiplication problem. Let me t(...TRUNCATED)
"To solve the long multiplication equation \\(3622 \\times 5165\\), we can break down the multiplier(...TRUNCATED)
true
"The provided solution correctly performs the long multiplication of 3622 and 5165 by breaking down (...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to multiply 3622 by 5165. Hmm, that's a p(...TRUNCATED)
875
1,636
761
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
7
6
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
[ "18707630", "18707630", "18707630", "18707630", "18707630", "18707630" ]
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
1
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
[ "Addition verification: 18,110,000 + 362,200 + 217,320 + 18,110 = 18,707,630" ]
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
9
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
[]
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
"What is the solution to the long multiplication equation below?\n\n6624 x 7409\n\nThink step by ste(...TRUNCATED)
49077216
"Okay, so I need to multiply 6624 by 7409. Hmm, that's a pretty big multiplication. Let me think abo(...TRUNCATED)
"To solve the long multiplication equation \\(6624 \\times 7409\\), we break down the multiplication(...TRUNCATED)
true
"The breakdown of the multiplication is accurately executed, and the final sum of the products yield(...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to multiply 6624 by 7409. Hmm, that's a p(...TRUNCATED)
1,346
2,091
745
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
8
3
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
[ "49077216", "49077216", "49077216" ]
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
4
"<thinking>\nLet's step through the reasoning trace to count how many times the model verifies an in(...TRUNCATED)
["26,496 x 100 = 2,649,600","49,017,600 + 59,616 = 49,077,216","6624 x 74 = 6624 x 70 + 6624 x 4 = 4(...TRUNCATED)
"<thinking>\nLet's step through the reasoning trace to count how many times the model verifies an in(...TRUNCATED)
7
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
[]
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
"What is the solution to the long multiplication equation below?\n\n2861 x 2656\n\nThink step by ste(...TRUNCATED)
7598816
"Okay, so I need to multiply 2861 by 2656. Hmm, that's a pretty big multiplication problem. Let me t(...TRUNCATED)
"To solve the long multiplication equation \\(2861 \\times 2656\\), we break down the multiplication(...TRUNCATED)
true
"The solution correctly breaks down the long multiplication into manageable parts, accurately calcul(...TRUNCATED)
[{"content":"You are a reasoning assistant. Given a chain-of-thought reasoning trace, output a JSON (...TRUNCATED)
[{"contains_final_answer":false,"content":"Okay, so I need to multiply 2861 by 2656. Hmm, that's a p(...TRUNCATED)
921
1,466
545
answer_verification
"How many times does the following reasoning trace propose a final answer then verify it or double c(...TRUNCATED)
9
4
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
[ "7598816", "7598816", "7598816", "7598816" ]
"<thinking>To determine how many times the model proposed a final answer, we look for each point in (...TRUNCATED)
4
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
["Verification of 6 x 2861 for the hundreds place partial product","Verification of addition 17166 +(...TRUNCATED)
"Let's step through the reasoning trace to count how many times the model verifies an intermediate c(...TRUNCATED)
6
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
[]
"<thinking>To answer your question—how many times does the model verify its higher-level reasoning(...TRUNCATED)
End of preview. Expand in Data Studio
README.md exists but content is empty.
Downloads last month
4