MMTU-benchmark/MMTU huggingface dataset:
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                          | B                  | C        | D                    |
|---:|:---------------------------|:-------------------|:---------|:---------------------|
|  1 | Ref+                       | 2.5                | V        |                      |
|  2 | Ref-                       | 0                  | V        |                      |
|  3 | Resolution                 | 1024               |          |                      |
|  4 | Step Size                  | [Target Cell]      | V        |                      |
|  5 |                            |                    |          |                      |
|  6 | Raw Conversion Output Code | Equivelent Voltage | Fxn      | Fxn * 1000           |
|  7 | 0                          | 0                  | 0        |                      |
|  8 | 1                          | 0.00244140625      | 3.51906  | 0.00351906           |
|  9 | 2                          | 0.0048828125       | 7.03812  | 0.00703812           |
| 10 | 3                          | 0.00732421875      | 10.55718 | 0.010557180000000001 |
| 11 | 4                          | 0.009765625        | 14.07624 | 0.01407624           |
| 12 | 5                          | 0.01220703125      | 17.5953  | 0.0175953            |
| 13 | 6                          | 0.0146484375       | 21.11436 | 0.021114360000000002 |
| 14 | 7                          | 0.01708984375      | 24.63342 | 0.02463342           |



min_row: 1
max_row: 14
min_col: 1
max_col: 4
target_cell_row_idx: 4
target_cell_col_idx: 2
target_cell_value: 0.00244140625
formula: =(B1-B2)/B3
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                          | B                  | C        | D                    |
|---:|:---------------------------|:-------------------|:---------|:---------------------|
|  1 | Ref+                       | 2.5                | V        |                      |
|  2 | Ref-                       | 0                  | V        |                      |
|  3 | Resolution                 | 1024               |          |                      |
|  4 | Step Size                  | 0.00244140625      | V        |                      |
|  5 |                            |                    |          |                      |
|  6 | Raw Conversion Output Code | Equivelent Voltage | Fxn      | Fxn * 1000           |
|  7 | 0                          | 0                  | 0        |                      |
|  8 | 1                          | 0.00244140625      | 3.51906  | [Target Cell]        |
|  9 | 2                          | 0.0048828125       | 7.03812  | 0.00703812           |
| 10 | 3                          | 0.00732421875      | 10.55718 | 0.010557180000000001 |
| 11 | 4                          | 0.009765625        | 14.07624 | 0.01407624           |
| 12 | 5                          | 0.01220703125      | 17.5953  | 0.0175953            |
| 13 | 6                          | 0.0146484375       | 21.11436 | 0.021114360000000002 |
| 14 | 7                          | 0.01708984375      | 24.63342 | 0.02463342           |
| 15 | 8                          | 0.01953125         | 28.15248 | 0.02815248           |
| 16 | 9                          | 0.02197265625      | 31.67154 | 0.03167154           |
| 17 | 10                         | 0.0244140625       | 35.1906  | 0.0351906            |
| 18 | 11                         | 0.02685546875      | 38.70966 | 0.03870966           |



min_row: 1
max_row: 18
min_col: 1
max_col: 4
target_cell_row_idx: 8
target_cell_col_idx: 4
target_cell_value: 0.00351906
formula: =C8/1000
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                          | B                  | C             | D                    |
|---:|:---------------------------|:-------------------|:--------------|:---------------------|
|  1 | Ref+                       | 2.5                | V             |                      |
|  2 | Ref-                       | 0                  | V             |                      |
|  3 | Resolution                 | 1024               |               |                      |
|  4 | Step Size                  | 0.00244140625      | V             |                      |
|  5 |                            |                    |               |                      |
|  6 | Raw Conversion Output Code | Equivelent Voltage | Fxn           | Fxn * 1000           |
|  7 | 0                          | 0                  | [Target Cell] |                      |
|  8 | 1                          | 0.00244140625      | 3.51906       | 0.00351906           |
|  9 | 2                          | 0.0048828125       | 7.03812       | 0.00703812           |
| 10 | 3                          | 0.00732421875      | 10.55718      | 0.010557180000000001 |
| 11 | 4                          | 0.009765625        | 14.07624      | 0.01407624           |
| 12 | 5                          | 0.01220703125      | 17.5953       | 0.0175953            |
| 13 | 6                          | 0.0146484375       | 21.11436      | 0.021114360000000002 |
| 14 | 7                          | 0.01708984375      | 24.63342      | 0.02463342           |
| 15 | 8                          | 0.01953125         | 28.15248      | 0.02815248           |
| 16 | 9                          | 0.02197265625      | 31.67154      | 0.03167154           |
| 17 | 10                         | 0.0244140625       | 35.1906       | 0.0351906            |



min_row: 1
max_row: 17
min_col: 1
max_col: 4
target_cell_row_idx: 7
target_cell_col_idx: 3
target_cell_value: 0
formula: =(A7*3.51906)
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A   | B         | C             | D    |
|---:|:----|:----------|:--------------|:-----|
| 34 |     |           |               |      |
| 35 |     | RefDes    | Value         | Unit |
| 36 |     | RBLKupper | 14.97         | MΩ   |
| 37 |     | RBLKlower | 41.2          | kΩ   |
| 38 |     | RBWupper  | 31.6          | KΩ   |
| 39 |     | RBWlower  | 5.36          | KΩ   |
| 40 |     | CISNS     | 150           | pF   |
| 41 |     | RISNS     | 147           | Ω    |
| 42 |     | CVCRupper | 68            | pF   |
| 43 |     | CVCRlower | 8200          | pF   |
| 44 |     | Lr        | [Target Cell] | uH   |
| 45 |     | Lm        | 450           | uH   |
| 46 |     | Cr        | 0.0244        | uF   |
| 47 |     | CSS       | 68            | nF   |
| 48 |     | RLLupper  | 332           | KΩ   |
| 49 |     | RLLlower  | 267           | KΩ   |



min_row: 34
max_row: 49
min_col: 1
max_col: 4
target_cell_row_idx: 44
target_cell_col_idx: 3
target_cell_value: 95
formula: =Lr
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                          | B                  | C        | D                    |
|---:|:---------------------------|:-------------------|:---------|:---------------------|
|  1 | Ref+                       | 2.5                | V        |                      |
|  2 | Ref-                       | 0                  | V        |                      |
|  3 | Resolution                 | 1024               |          |                      |
|  4 | Step Size                  | 0.00244140625      | V        |                      |
|  5 |                            |                    |          |                      |
|  6 | Raw Conversion Output Code | Equivelent Voltage | Fxn      | Fxn * 1000           |
|  7 | 0                          | [Target Cell]      | 0        |                      |
|  8 | 1                          | 0.00244140625      | 3.51906  | 0.00351906           |
|  9 | 2                          | 0.0048828125       | 7.03812  | 0.00703812           |
| 10 | 3                          | 0.00732421875      | 10.55718 | 0.010557180000000001 |
| 11 | 4                          | 0.009765625        | 14.07624 | 0.01407624           |
| 12 | 5                          | 0.01220703125      | 17.5953  | 0.0175953            |
| 13 | 6                          | 0.0146484375       | 21.11436 | 0.021114360000000002 |
| 14 | 7                          | 0.01708984375      | 24.63342 | 0.02463342           |
| 15 | 8                          | 0.01953125         | 28.15248 | 0.02815248           |
| 16 | 9                          | 0.02197265625      | 31.67154 | 0.03167154           |
| 17 | 10                         | 0.0244140625       | 35.1906  | 0.0351906            |



min_row: 1
max_row: 17
min_col: 1
max_col: 4
target_cell_row_idx: 7
target_cell_col_idx: 2
target_cell_value: 0
formula: =($B$2+(A7*$B$4))
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B              | C               | D              |
|---:|:--------------------------------------|:---------------|:----------------|:---------------|
|  1 | VCM=12V                               |                |                 |                |
|  2 | Vin(MV)                               | Vout_Ideal(MV) | Vout_Actual(MV) | Vout_Error(MV) |
|  3 | 20                                    | 2000           | 2001            | [Target Cell]  |
|  4 | 60                                    | 6000           | 6007            | 4.75           |
|  5 | 100                                   | 10000          | 10004           | 0.25           |
|  6 |                                       |                |                 |                |
|  7 | Gain                                  |                |                 |                |
|  8 | 100.0375                              |                |                 |                |
|  9 | Ideal average error over input range  |                |                 |                |
| 10 | 0.25                                  |                |                 |                |
| 11 | Mid-point error difference from Ideal |                |                 |                |
| 12 | 4.5                                   |                |                 |                |
| 13 | Nonlinearity in %                     |                |                 |                |



min_row: 1
max_row: 13
min_col: 1
max_col: 4
target_cell_row_idx: 3
target_cell_col_idx: 4
target_cell_value: 0.25
formula: =C3-A3*$A$8
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B              | C               | D              |
|---:|:--------------------------------------|:---------------|:----------------|:---------------|
|  1 | VCM=12V                               |                |                 |                |
|  2 | Vin(MV)                               | Vout_Ideal(MV) | Vout_Actual(MV) | Vout_Error(MV) |
|  3 | 20                                    | [Target Cell]  | 2001            | 0.25           |
|  4 | 60                                    | 6000           | 6007            | 4.75           |
|  5 | 100                                   | 10000          | 10004           | 0.25           |
|  6 |                                       |                |                 |                |
|  7 | Gain                                  |                |                 |                |
|  8 | 100.0375                              |                |                 |                |
|  9 | Ideal average error over input range  |                |                 |                |
| 10 | 0.25                                  |                |                 |                |
| 11 | Mid-point error difference from Ideal |                |                 |                |
| 12 | 4.5                                   |                |                 |                |
| 13 | Nonlinearity in %                     |                |                 |                |



min_row: 1
max_row: 13
min_col: 1
max_col: 4
target_cell_row_idx: 3
target_cell_col_idx: 2
target_cell_value: 2000
formula: =A3*100
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B              | C               | D              |
|---:|:--------------------------------------|:---------------|:----------------|:---------------|
|  1 | VCM=12V                               |                |                 |                |
|  2 | Vin(MV)                               | Vout_Ideal(MV) | Vout_Actual(MV) | Vout_Error(MV) |
|  3 | 20                                    | 2000           | 2001            | 0.25           |
|  4 | 60                                    | 6000           | [Target Cell]   | 4.75           |
|  5 | 100                                   | 10000          | 10004           | 0.25           |
|  6 |                                       |                |                 |                |
|  7 | Gain                                  |                |                 |                |
|  8 | 100.0375                              |                |                 |                |
|  9 | Ideal average error over input range  |                |                 |                |
| 10 | 0.25                                  |                |                 |                |
| 11 | Mid-point error difference from Ideal |                |                 |                |
| 12 | 4.5                                   |                |                 |                |
| 13 | Nonlinearity in %                     |                |                 |                |
| 14 | 0.02811445707859553                   |                |                 |                |



min_row: 1
max_row: 14
min_col: 1
max_col: 4
target_cell_row_idx: 4
target_cell_col_idx: 3
target_cell_value: 6007
formula: =A4*100+7
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B              | C               | D              |
|---:|:--------------------------------------|:---------------|:----------------|:---------------|
|  1 | VCM=12V                               |                |                 |                |
|  2 | Vin(MV)                               | Vout_Ideal(MV) | Vout_Actual(MV) | Vout_Error(MV) |
|  3 | 20                                    | 2000           | 2001            | 0.25           |
|  4 | 60                                    | 6000           | 6007            | 4.75           |
|  5 | 100                                   | 10000          | [Target Cell]   | 0.25           |
|  6 |                                       |                |                 |                |
|  7 | Gain                                  |                |                 |                |
|  8 | 100.0375                              |                |                 |                |
|  9 | Ideal average error over input range  |                |                 |                |
| 10 | 0.25                                  |                |                 |                |
| 11 | Mid-point error difference from Ideal |                |                 |                |
| 12 | 4.5                                   |                |                 |                |
| 13 | Nonlinearity in %                     |                |                 |                |
| 14 | 0.02811445707859553                   |                |                 |                |



min_row: 1
max_row: 14
min_col: 1
max_col: 4
target_cell_row_idx: 5
target_cell_col_idx: 3
target_cell_value: 10004
formula: =A5*100+4
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B       | C       | D    |
|---:|:--------------------------------------|:--------|:--------|:-----|
|  4 | 60                                    | 6000.0  | 6007.0  | 4.75 |
|  5 | 100                                   | 10000.0 | 10004.0 | 0.25 |
|  6 |                                       |         |         |      |
|  7 | Gain                                  |         |         |      |
|  8 | 100.0375                              |         |         |      |
|  9 | Ideal average error over input range  |         |         |      |
| 10 | 0.25                                  |         |         |      |
| 11 | Mid-point error difference from Ideal |         |         |      |
| 12 | 4.5                                   |         |         |      |
| 13 | Nonlinearity in %                     |         |         |      |
| 14 | [Target Cell]                         |         |         |      |



min_row: 4
max_row: 14
min_col: 1
max_col: 4
target_cell_row_idx: 14
target_cell_col_idx: 1
target_cell_value: 0.02811445707859553
formula: =A12/2/(C5-C3)*100
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B              | C               | D              |
|---:|:--------------------------------------|:---------------|:----------------|:---------------|
|  1 | VCM=12V                               |                |                 |                |
|  2 | Vin(MV)                               | Vout_Ideal(MV) | Vout_Actual(MV) | Vout_Error(MV) |
|  3 | 20                                    | 2000           | 2001            | 0.25           |
|  4 | 60                                    | 6000           | 6007            | 4.75           |
|  5 | 100                                   | 10000          | 10004           | 0.25           |
|  6 |                                       |                |                 |                |
|  7 | Gain                                  |                |                 |                |
|  8 | [Target Cell]                         |                |                 |                |
|  9 | Ideal average error over input range  |                |                 |                |
| 10 | 0.25                                  |                |                 |                |
| 11 | Mid-point error difference from Ideal |                |                 |                |
| 12 | 4.5                                   |                |                 |                |
| 13 | Nonlinearity in %                     |                |                 |                |
| 14 | 0.02811445707859553                   |                |                 |                |



min_row: 1
max_row: 14
min_col: 1
max_col: 4
target_cell_row_idx: 8
target_cell_col_idx: 1
target_cell_value: 100.0375
formula: =(C5-C3)/(A5-A3)
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B              | C               | D              |
|---:|:--------------------------------------|:---------------|:----------------|:---------------|
|  1 | VCM=12V                               |                |                 |                |
|  2 | Vin(MV)                               | Vout_Ideal(MV) | Vout_Actual(MV) | Vout_Error(MV) |
|  3 | 20                                    | 2000           | [Target Cell]   | 0.25           |
|  4 | 60                                    | 6000           | 6007            | 4.75           |
|  5 | 100                                   | 10000          | 10004           | 0.25           |
|  6 |                                       |                |                 |                |
|  7 | Gain                                  |                |                 |                |
|  8 | 100.0375                              |                |                 |                |
|  9 | Ideal average error over input range  |                |                 |                |
| 10 | 0.25                                  |                |                 |                |
| 11 | Mid-point error difference from Ideal |                |                 |                |
| 12 | 4.5                                   |                |                 |                |
| 13 | Nonlinearity in %                     |                |                 |                |



min_row: 1
max_row: 13
min_col: 1
max_col: 4
target_cell_row_idx: 3
target_cell_col_idx: 3
target_cell_value: 2001
formula: =A3*100+1
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                   |
|---:|:--------------------|
| 12 | -0.15643  0.98769   |
| 13 | -0.30902  0.95106   |
| 14 | -0.45399  0.89101   |
| 15 | -0.58778  0.80902   |
| 16 | -0.70711  0.70711   |
| 17 | -0.80902  0.58778   |
| 18 | -0.89101  0.45399   |
| 19 | -0.95106  0.30902   |
| 20 | -0.98769  0.15643   |
| 21 | -1  0               |
| 22 | [Target Cell]       |
| 23 | -1.26008            |
| 24 | -1.345              |
| 25 | -1.3967999999999998 |
| 26 | -1.41422            |
| 27 | -1.3967999999999998 |
| 28 | -1.345              |
| 29 | -1.26008            |
| 30 | -1.14412            |
| 31 | 7.7439008  -1       |
| 32 | 0.15643  -0.98769   |



min_row: 12
max_row: 32
min_col: 1
max_col: 1
target_cell_row_idx: 22
target_cell_col_idx: 1
target_cell_value: -1.14412
formula: =-0.98769  -0.15643
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                   |
|---:|:--------------------|
| 52 | -0.15643  0.98769   |
| 53 | -0.30902  0.95106   |
| 54 | -0.45399  0.89101   |
| 55 | -0.58778  0.80902   |
| 56 | -0.70711  0.70711   |
| 57 | -0.80902  0.58778   |
| 58 | -0.89101  0.45399   |
| 59 | -0.95106  0.30902   |
| 60 | -0.98769  0.15643   |
| 61 | -1  0               |
| 62 | [Target Cell]       |
| 63 | -1.26008            |
| 64 | -1.345              |
| 65 | -1.3967999999999998 |
| 66 | -1.41422            |
| 67 | -1.3967999999999998 |
| 68 | -1.345              |
| 69 | -1.26008            |
| 70 | -1.14412            |
| 71 | 1.7106007  -1       |
| 72 | 0.15643  -0.98769   |



min_row: 52
max_row: 72
min_col: 1
max_col: 1
target_cell_row_idx: 62
target_cell_col_idx: 1
target_cell_value: -1.14412
formula: =-0.98769  -0.15643
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B              | C               | D              |
|---:|:--------------------------------------|:---------------|:----------------|:---------------|
|  2 | Vin(MV)                               | Vout_Ideal(MV) | Vout_Actual(MV) | Vout_Error(MV) |
|  3 | 20                                    | 2000           | 2001            | 0.25           |
|  4 | 60                                    | 6000           | 6007            | 4.75           |
|  5 | 100                                   | 10000          | 10004           | 0.25           |
|  6 |                                       |                |                 |                |
|  7 | Gain                                  |                |                 |                |
|  8 | 100.0375                              |                |                 |                |
|  9 | Ideal average error over input range  |                |                 |                |
| 10 | 0.25                                  |                |                 |                |
| 11 | Mid-point error difference from Ideal |                |                 |                |
| 12 | [Target Cell]                         |                |                 |                |
| 13 | Nonlinearity in %                     |                |                 |                |
| 14 | 0.02811445707859553                   |                |                 |                |



min_row: 2
max_row: 14
min_col: 1
max_col: 4
target_cell_row_idx: 12
target_cell_col_idx: 1
target_cell_value: 4.5
formula: =D4-A10
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|     | A                   |
|----:|:--------------------|
|  92 | -0.15643  0.98769   |
|  93 | -0.30902  0.95106   |
|  94 | -0.45399  0.89101   |
|  95 | -0.58778  0.80902   |
|  96 | -0.70711  0.70711   |
|  97 | -0.80902  0.58778   |
|  98 | -0.89101  0.45399   |
|  99 | -0.95106  0.30902   |
| 100 | -0.98769  0.15643   |
| 101 | -5.7684007          |
| 102 | [Target Cell]       |
| 103 | -1.26008            |
| 104 | -1.345              |
| 105 | -1.3967999999999998 |
| 106 | -1.41422            |
| 107 | -1.3967999999999998 |
| 108 | -1.345              |
| 109 | -1.26008            |
| 110 | -1.14412            |
| 111 | 2.6469007  -1       |
| 112 | 0.15643  -0.98769   |



min_row: 92
max_row: 112
min_col: 1
max_col: 1
target_cell_row_idx: 102
target_cell_col_idx: 1
target_cell_value: -1.14412
formula: =-0.98769  -0.15643
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|     | A                   |
|----:|:--------------------|
| 132 | -0.15643  0.98769   |
| 133 | -0.30902  0.95106   |
| 134 | -0.45399  0.89101   |
| 135 | -0.58778  0.80902   |
| 136 | -0.70711  0.70711   |
| 137 | -0.80902  0.58778   |
| 138 | -0.89101  0.45399   |
| 139 | -0.95106  0.30902   |
| 140 | -0.98769  0.15643   |
| 141 | -5.7684007          |
| 142 | [Target Cell]       |
| 143 | -1.26008            |
| 144 | -1.345              |
| 145 | -1.3967999999999998 |
| 146 | -1.41422            |
| 147 | -1.3967999999999998 |
| 148 | -1.345              |
| 149 | -1.26008            |
| 150 | -1.14412            |
| 151 | 3.5832007  -1       |
| 152 | 0.15643  -0.98769   |



min_row: 132
max_row: 152
min_col: 1
max_col: 1
target_cell_row_idx: 142
target_cell_col_idx: 1
target_cell_value: -1.14412
formula: =-0.98769  -0.15643
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                                     | B              | C               | D              |
|---:|:--------------------------------------|:---------------|:----------------|:---------------|
|  1 | VCM=12V                               |                |                 |                |
|  2 | Vin(MV)                               | Vout_Ideal(MV) | Vout_Actual(MV) | Vout_Error(MV) |
|  3 | 20                                    | 2000           | 2001            | 0.25           |
|  4 | 60                                    | 6000           | 6007            | 4.75           |
|  5 | 100                                   | 10000          | 10004           | 0.25           |
|  6 |                                       |                |                 |                |
|  7 | Gain                                  |                |                 |                |
|  8 | 100.0375                              |                |                 |                |
|  9 | Ideal average error over input range  |                |                 |                |
| 10 | [Target Cell]                         |                |                 |                |
| 11 | Mid-point error difference from Ideal |                |                 |                |
| 12 | 4.5                                   |                |                 |                |
| 13 | Nonlinearity in %                     |                |                 |                |
| 14 | 0.02811445707859553                   |                |                 |                |



min_row: 1
max_row: 14
min_col: 1
max_col: 4
target_cell_row_idx: 10
target_cell_col_idx: 1
target_cell_value: 0.25
formula: =(D3+D5)/2
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    | A                 | B             |
|---:|:------------------|:--------------|
|  1 | fosc              | 38400000      |
|  2 | Decimation Factor | 20            |
|  3 | AGC_SETTLE _WAIT  | 1             |
|  4 | BB_CIC_DECFACT    | 14            |
|  5 | AGC WIN SIZE      | 3             |
|  6 | T2                | [Target Cell] |



min_row: 1
max_row: 6
min_col: 1
max_col: 2
target_cell_row_idx: 6
target_cell_col_idx: 2
target_cell_value: 0.00093453125
formula: =((2^(B5+4))*B4*B2+46)/B1
Task: Formula-prediction-context (source dataset: ti-random)

You are given an table region extracted from a real Excel spreadsheet, which is centered around a cell called "Target Cell" (labeled as "[Target Cell]" shown in the table below). The table region below includes up to 10 rows above/below the Target Cell, and 10 columns to the left/right of the Target Cell. 

Your task is to analyze the table context surrounding the Target Cell, and predict the most likely Excel formula that should go in the Target Cell. If multiple formulas are possible, choose the most reasonable or commonly used based on context.

1. Please follow the standard formula syntax in Excel, e.g. always begins with an equal sign (=).
2. Base your predicted formula on the surrounding table context, e.g., column headers, annotations, and data values in nearby cells.
3. No explanation — just output the formula itself in a JSON format: {"formula": "your_formula_here"}.

Input Excel Snippet in Markdown format:
|    |   A |       B | C   | D          | E             |
|---:|----:|--------:|:----|:-----------|:--------------|
|  1 |   0 | 1135494 |     | Max        | 1136222       |
|  2 |   1 | 1135752 |     | Min        | 1132910       |
|  3 |   2 | 1135630 |     | Difference | [Target Cell] |
|  4 |   3 | 1135327 |     |            |               |
|  5 |   4 | 1135466 |     |            |               |
|  6 |   5 | 1135376 |     |            |               |
|  7 |   6 | 1135489 |     |            |               |
|  8 |   7 | 1135653 |     |            |               |
|  9 |   8 | 1135668 |     |            |               |
| 10 |   9 | 1135858 |     |            |               |
| 11 |  10 | 1136086 |     |            |               |
| 12 |  11 | 1135803 |     |            |               |
| 13 |  12 | 1135765 |     |            |               |



min_row: 1
max_row: 13
min_col: 1
max_col: 5
target_cell_row_idx: 3
target_cell_col_idx: 5
target_cell_value: 3312
formula: =E1-E2