MMTU-benchmark/MMTU huggingface dataset:
Task: Formula-prediction-context (source dataset: cisco-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      |         F | G             |
|---:|:---------------------------------------------------|:----------------|:----------|----------:|:-------|----------:|:--------------|
|  1 | cdx01as38#sh spanning-tree vlan 1 detail | in sent |                 |           | 570906520 |        | 403483675 | [Target Cell] |
|  2 | BPDU: sent 22032132                                | received 8457   | 22032132  |  22032132 | 8457   |      8457 |               |
|  3 | BPDU: sent 713308                                  | received 17     | 713308    |    713308 | 17     |        17 |               |
|  4 | BPDU: sent 570877636                               | received 0      | 570877636 | 570877636 | 0      |         0 |               |
|  5 | BPDU: sent 15945149                                | received 0      | 15945149  |  15945149 | 0      |         0 |               |
|  6 | BPDU: sent 152148457                               | received 0      | 152148457 | 152148457 | 0      |         0 |               |
|  7 | BPDU: sent 22035383                                | received 109    | 22035383  |  22035383 | 109    |       109 |               |
|  8 | BPDU: sent 21771881                                | received 675865 | 21771881  |  21771881 | 675865 |    675865 |               |
|  9 | BPDU: sent 22032951                                | received 4865   | 22032951  |  22032951 | 4865   |      4865 |               |
| 10 | BPDU: sent 22035360                                | received 2      | 22035360  |  22035360 | 2      |         2 |               |
| 11 | BPDU: sent 22031357                                | received 8812   | 22031357  |  22031357 | 8812   |      8812 |               |



min_row: 1
max_row: 11
min_col: 1
max_col: 7
target_cell_row_idx: 1
target_cell_col_idx: 7
target_cell_value: 1
formula: =IF(D1>F1,1,0)
Task: Formula-prediction-context (source dataset: cisco-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             |         F | G   |
|---:|:---------------------------------------------------|:----------------|:----------|----------:|:--------------|----------:|:----|
|  1 | cdx01as38#sh spanning-tree vlan 1 detail | in sent |                 |           | 570906520 |               | 403483675 | 1.0 |
|  2 | BPDU: sent 22032132                                | received 8457   | 22032132  |  22032132 | [Target Cell] |      8457 |     |
|  3 | BPDU: sent 713308                                  | received 17     | 713308    |    713308 | 17            |        17 |     |
|  4 | BPDU: sent 570877636                               | received 0      | 570877636 | 570877636 | 0             |         0 |     |
|  5 | BPDU: sent 15945149                                | received 0      | 15945149  |  15945149 | 0             |         0 |     |
|  6 | BPDU: sent 152148457                               | received 0      | 152148457 | 152148457 | 0             |         0 |     |
|  7 | BPDU: sent 22035383                                | received 109    | 22035383  |  22035383 | 109           |       109 |     |
|  8 | BPDU: sent 21771881                                | received 675865 | 21771881  |  21771881 | 675865        |    675865 |     |
|  9 | BPDU: sent 22032951                                | received 4865   | 22032951  |  22032951 | 4865          |      4865 |     |
| 10 | BPDU: sent 22035360                                | received 2      | 22035360  |  22035360 | 2             |         2 |     |
| 11 | BPDU: sent 22031357                                | received 8812   | 22031357  |  22031357 | 8812          |      8812 |     |
| 12 | BPDU: sent 22035364                                | received 3      | 22035364  |  22035364 | 3             |         3 |     |



min_row: 1
max_row: 12
min_col: 1
max_col: 7
target_cell_row_idx: 2
target_cell_col_idx: 5
target_cell_value: 8457
formula: =MID(B2,11,16)
Task: Formula-prediction-context (source dataset: cisco-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      | F             | G   |
|---:|:---------------------------------------------------|:----------------|:----------|----------:|:-------|:--------------|:----|
|  1 | cdx01as38#sh spanning-tree vlan 1 detail | in sent |                 |           | 570906520 |        | 403483675     | 1.0 |
|  2 | BPDU: sent 22032132                                | received 8457   | 22032132  |  22032132 | 8457   | [Target Cell] |     |
|  3 | BPDU: sent 713308                                  | received 17     | 713308    |    713308 | 17     | 17            |     |
|  4 | BPDU: sent 570877636                               | received 0      | 570877636 | 570877636 | 0      | 0             |     |
|  5 | BPDU: sent 15945149                                | received 0      | 15945149  |  15945149 | 0      | 0             |     |
|  6 | BPDU: sent 152148457                               | received 0      | 152148457 | 152148457 | 0      | 0             |     |
|  7 | BPDU: sent 22035383                                | received 109    | 22035383  |  22035383 | 109    | 109           |     |
|  8 | BPDU: sent 21771881                                | received 675865 | 21771881  |  21771881 | 675865 | 675865        |     |
|  9 | BPDU: sent 22032951                                | received 4865   | 22032951  |  22032951 | 4865   | 4865          |     |
| 10 | BPDU: sent 22035360                                | received 2      | 22035360  |  22035360 | 2      | 2             |     |
| 11 | BPDU: sent 22031357                                | received 8812   | 22031357  |  22031357 | 8812   | 8812          |     |
| 12 | BPDU: sent 22035364                                | received 3      | 22035364  |  22035364 | 3      | 3             |     |



min_row: 1
max_row: 12
min_col: 1
max_col: 7
target_cell_row_idx: 2
target_cell_col_idx: 6
target_cell_value: 8457
formula: =IF(ISERROR(_xlfn.NUMBERVALUE(TRIM(E2))),0,_xlfn.NUMBERVALUE(TRIM(E2)))
Task: Formula-prediction-context (source dataset: cisco-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      |         F | G   |
|---:|:---------------------------------------------------|:----------------|:----------|:--------------|:-------|----------:|:----|
|  1 | cdx01as38#sh spanning-tree vlan 1 detail | in sent |                 |           | 570906520     |        | 403483675 | 1.0 |
|  2 | BPDU: sent 22032132                                | received 8457   | 22032132  | [Target Cell] | 8457   |      8457 |     |
|  3 | BPDU: sent 713308                                  | received 17     | 713308    | 713308        | 17     |        17 |     |
|  4 | BPDU: sent 570877636                               | received 0      | 570877636 | 570877636     | 0      |         0 |     |
|  5 | BPDU: sent 15945149                                | received 0      | 15945149  | 15945149      | 0      |         0 |     |
|  6 | BPDU: sent 152148457                               | received 0      | 152148457 | 152148457     | 0      |         0 |     |
|  7 | BPDU: sent 22035383                                | received 109    | 22035383  | 22035383      | 109    |       109 |     |
|  8 | BPDU: sent 21771881                                | received 675865 | 21771881  | 21771881      | 675865 |    675865 |     |
|  9 | BPDU: sent 22032951                                | received 4865   | 22032951  | 22032951      | 4865   |      4865 |     |
| 10 | BPDU: sent 22035360                                | received 2      | 22035360  | 22035360      | 2      |         2 |     |
| 11 | BPDU: sent 22031357                                | received 8812   | 22031357  | 22031357      | 8812   |      8812 |     |
| 12 | BPDU: sent 22035364                                | received 3      | 22035364  | 22035364      | 3      |         3 |     |



min_row: 1
max_row: 12
min_col: 1
max_col: 7
target_cell_row_idx: 2
target_cell_col_idx: 4
target_cell_value: 22032132
formula: =IF(ISERROR(_xlfn.NUMBERVALUE(TRIM(C2))),0,_xlfn.NUMBERVALUE(TRIM(C2)))
Task: Formula-prediction-context (source dataset: cisco-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       | F        | G        | H       | I     | J      | K     | L    | M       | N       |
|---:|:----|:----------------------|:---------|:--------------|:--------|:---------|:---------|:--------|:------|:-------|:------|:-----|:--------|:--------|
|  1 |     |                       | 1        | [Target Cell] | 3       | 4        | 5        | 6       | 7     | 8      | 9     | 10   | 11      | 12      |
|  2 | #   | Question              | Softbank | KDDI          | DT      | Swisscom | NTT-East | NTT-Doc | Vz IT | Vz MNS | Spark | AT&T | Ooredoo | Telstra |
|  3 | 1   | VNFs on Openstack     | No       | Yes           | Yes     | Yes      | Yes      | Yes     | No    | Yes    | No    | Yes  | Yes     | Yes     |
|  4 | 2   | VMware vCenter as VIM | Yes      | No            | n/a     | Yes      | No       | No      | Yes   | Yes    | Yes   | No   | Yes     | Yes     |
|  5 | 3   | vCloud Dir vs vCenter | No       | n/a           | n/a     | Yes      | No       | No      | Dep   | Dep    | No    | No   | Yes     | No      |
|  6 | 4   | VNFs on AWS           | No       | Yes           | n/a     | No       | No       | No      | Yes   | Yes    | No    | Dep  | No      | Yes     |
|  7 |     |                       |          |               |         |          |          |         |       |        |       |      |         |         |
|  8 |     |                       |          |               |         |          |          |         |       |        |       |      |         |         |
|  9 | #   | Question              | Yes      | No            | Depends | n/a      | Checksum |         |       |        |       |      |         |         |
| 10 | 1   | VNFs on Openstack     | 28       | 5             | 2       | 0        | 35       |         |       |        |       |      |         |         |
| 11 | 2   | VMware vCenter as VIM | 19       | 14            | 1       | 1        | 35       |         |       |        |       |      |         |         |



min_row: 1
max_row: 11
min_col: 1
max_col: 14
target_cell_row_idx: 1
target_cell_col_idx: 4
target_cell_value: 2
formula: =C1+1
Task: Formula-prediction-context (source dataset: cisco-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   | F   |
|----:|:-----|:-----------------|:----------------------|:----|:----|:----|
| 149 |      |                  | VNFs on AWS           |     |     |     |
| 150 | 38.0 | Who is next?     | VNFs on Openstack     |     |     |     |
| 151 |      |                  | VMware vCenter as VIM |     |     |     |
| 152 |      |                  | vCloud Dir vs vCenter |     |     |     |
| 153 |      |                  | VNFs on AWS           |     |     |     |
| 154 |      |                  |                       |     |     |     |
| 155 |      |                  |                       |     |     |     |
| 156 |      |                  |                       |     |     |     |
| 157 |      |                  |                       |     |     |     |
| 158 |      | Geo distribution |                       |     |     |     |
| 159 |      | APJ              | [Target Cell]         |     |     |     |
| 160 |      | US               | 7                     |     |     |     |
| 161 |      | EMEAR            | 13                    |     |     |     |
| 162 |      | China            | 3                     |     |     |     |
| 163 |      | Latam            | 2                     |     |     |     |
| 164 |      |                  | 35                    |     |     |     |
| 165 |      |                  |                       |     |     |     |
| 166 |      |                  |                       |     |     |     |
| 167 |      |                  |                       |     |     |     |
| 168 |      |                  |                       |     |     |     |
| 169 |      |                  |                       |     |     |     |



min_row: 149
max_row: 169
min_col: 1
max_col: 6
target_cell_row_idx: 159
target_cell_col_idx: 3
target_cell_value: 10
formula: =COUNTIF(E2:E153,"APJ")/4
Task: Formula-prediction-context (source dataset: cisco-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 | Product           | Product Description                               | Price | State of Florida Purchase Price |
|  2 | CON-CBNT-2821SRST | COLL 8x5xNBD INT, 2821 Voice Bundle               | 634   | [Target Cell]                   |
|  3 | CON-CBNT-C2801SRS | COLL 8x5xNBD INT, 2801 Voice Bundle               | 378   | 321.3                           |
|  4 | CON-CBNT-C2801VK  | COLL 8x5xNBD INT, 2801 Voice Bndle,PVDM2          | 315   | 267.75                          |
|  5 | CON-CBNT-C2811SRS | COLL 8x5xNBD INT, 2811 Voice Bundle               | 504   | 428.4                           |
|  6 | CON-CBNT-C2811V9  | COLL 8x5xNBD INT, 2811 Voice Bundle,PV            | 420   | 357                             |
|  7 | CON-CBNT-C2851SRS | COLL 8x5xNBD INT, 2851 Voice Bundle               | 876   | 744.6                           |
|  8 | CON-CC4T-CTMS1.5  | 2TIER ESS 24X7X4OS TelePres Exp Multipoint Switch | 14160 | 12036                           |
|  9 | CON-CC4T-CTS1310P | 2TIER ESS 24X7X4OS CTS-1300-65 10 unit            | 15549 | 13216.65                        |
| 10 | CON-CC4T-CTS1365  | 2TIER ESS 24X7X4OS TelePresence 1300-65           | 17625 | 14981.25                        |
| 11 | CON-CC4T-CTSC1K   | 2TIER ESS 24X7X4OS Cisco TelePres Exp 1000 System | 17064 | 14504.4                         |
| 12 | CON-CC4T-CTSC500  | 2TIER ESS 24X7X4OS Cisco TelePres Exp 500 System  | 6559  | 5575.15                         |



min_row: 1
max_row: 12
min_col: 1
max_col: 4
target_cell_row_idx: 2
target_cell_col_idx: 4
target_cell_value: 538.9
formula: =C2*0.85
Task: Formula-prediction-context (source dataset: cisco-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   |
|---:|:--------------------------------------|:------|:--------------|:----|
| 28 | CP-7942/62 (6.3W)                     | 6.3   | 0             | 0.0 |
| 29 | CP-7960G (6.3W)                       | 6.3   | 0             | 0.0 |
| 30 | CP-7965/45 (12W)                      | 12.0  | 0             | 0.0 |
| 31 | CP-7970G (10.25W)                     | 10.25 | 0             | 0.0 |
| 32 | CP-7971G (14.9W)                      | 14.9  | 0             | 0.0 |
| 33 | CP-7975 (12W)                         | 12.0  | 0             | 0.0 |
| 34 | IEEE 802.3af Device - Class 0 (15.4W) | 15.4  | 0             | 0.0 |
| 35 | IEEE 802.3af Device - Class 1 (4W)    | 4.0   | 0             | 0.0 |
| 36 | IEEE 802.3af Device - Class 2 (7W)    | 7.0   | 0             | 0.0 |
| 37 | IEEE 802.3af Device - Class 3 (15.4W) | 15.4  | 0             | 0.0 |
| 38 | Total                                 |       | [Target Cell] | 0.0 |
| 39 |                                       |       |               |     |
| 40 |                                       |       |               |     |
| 41 |                                       |       |               |     |
| 42 |                                       |       |               |     |
| 43 |                                       |       |               |     |



min_row: 28
max_row: 43
min_col: 1
max_col: 4
target_cell_row_idx: 38
target_cell_col_idx: 3
target_cell_value: 0
formula: =SUM(C6:C37)
Task: Formula-prediction-context (source dataset: cisco-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        | F             | G   | H   | I   |
|---:|:----|:----|:----|:----|:---------|:--------------|:----|:----|:----|
| 10 |     |     |     |     |          |               |     |     |     |
| 11 |     |     |     |     |          |               |     |     |     |
| 12 |     |     |     |     |          |               |     |     |     |
| 13 |     |     |     |     |          |               |     |     |     |
| 14 |     |     |     |     | Csipl    | 12            |     |     |     |
| 15 |     |     |     |     | Capital  | 4             |     |     |     |
| 16 |     |     |     |     | Ccipl    | 5             |     |     |     |
| 17 |     |     |     |     | Cvtipl   | 2             |     |     |     |
| 18 |     |     |     |     | Webex    | 1             |     |     |     |
| 19 |     |     |     |     | Acquired | 4             |     |     |     |
| 20 |     |     |     |     |          | [Target Cell] |     |     |     |



min_row: 10
max_row: 20
min_col: 1
max_col: 9
target_cell_row_idx: 20
target_cell_col_idx: 6
target_cell_value: 28
formula: =SUM(F14:F19)
Task: Formula-prediction-context (source dataset: cisco-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 |                                 |          |          |               |
|  2 | Cisco Power Calculator          |          |          |               |
|  3 |                                 |          |          |               |
|  4 | PoE Device Details              |          |          |               |
|  5 | PoE Device                      | Powered  | Quantity | Total         |
|    |                                 | Device   |          | Powered       |
|    |                                 | Output   |          | Device        |
|    |                                 | Power(W) |          | Output        |
|    |                                 |          |          | Power(W)      |
|  6 | 7906G - 0.119 amps (5W)         | 5        | 0        | [Target Cell] |
|  7 | 7911G - 0.119 amps (5W)         | 5        | 0        | 0             |
|  8 | 7941G - 0.15 amps (6.3W)        | 6.3      | 0        | 0             |
|  9 | 7941G-GE - 0.3071 amps (12.9W)  | 12.9     | 0        | 0             |
| 10 | 7961G - 0.15 amps (6.3W)        | 6.3      | 0        | 0             |
| 11 | 7961G-GE - 0.3071 amps (12.9W)  | 12.9     |          | 0             |
| 12 | 7971-G-GE- 0.3666 amps (15.4W)  | 15.4     |          | 0             |
| 13 | 7985G - 0.2988 amps (12.55W)    | 12.55    |          | 0             |
| 14 | AP-1100 with b/g radio (4.9W)   | 4.9      | 0        | 0             |
| 15 | AP-1200 with a radio (8.5W)     | 8.5      | 0        | 0             |
| 16 | AP-1200 with a+b radios (11.6W) | 11.6     | 0        | 0             |



min_row: 1
max_row: 16
min_col: 1
max_col: 4
target_cell_row_idx: 6
target_cell_col_idx: 4
target_cell_value: 0
formula: =B6*C6
Task: Formula-prediction-context (source dataset: cisco-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   | F   | G             | H   |
|---:|:-------------------------------------------------------|:----|:----|:----|:----|:----|:--------------|:----|
| 48 | Cisco Unified Presence Server End User Feature License | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0             |     |
| 49 | Cisco VGC Phone                                        | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0             |     |
| 50 | Cisco VGC Virtual Phone                                | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0             |     |
| 51 | H.323 Client                                           | 2.0 | 2.0 | 2.0 | 2.0 | 0.0 | 0             |     |
| 52 | IP-STE                                                 | 6.0 | 6.0 | 6.0 | 6.0 | 0.0 | 0             |     |
| 53 | Mobility Enabled End Users                             |     |     | 2.0 | 4.0 | 0.0 | 0             |     |
| 54 | Mobility Enabled End Users(Adjunct)                    |     |     |     | 2.0 | 0.0 | 0             |     |
| 55 | Other Phone                                            | 5.0 | 5.0 | 5.0 | 5.0 | 0.0 | 0             |     |
| 56 | Third-party SIP Device (Advanced)                      | 6.0 | 6.0 | 6.0 | 6.0 | 0.0 | 0             |     |
| 57 | Third-party SIP Device (Basic)                         | 3.0 | 3.0 | 3.0 | 3.0 | 0.0 | 0             |     |
| 58 | Total Phone License Units Needed:                      |     |     |     |     |     | [Target Cell] |     |



min_row: 48
max_row: 58
min_col: 1
max_col: 8
target_cell_row_idx: 58
target_cell_col_idx: 7
target_cell_value: 0
formula: =SUM(G15:G57)
Task: Formula-prediction-context (source dataset: pge-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 | F   | G   | H   |
|---:|----:|:------|:--------------------------------------------------|:--------------------|-----------------:|:----|:----|:----|
| 19 | 110 | 589   | Rents                                             | 0                   |      0           |     |     |     |
| 20 | 111 | 590   | Maintenance Supervision and Engineering           | 0                   |      0           |     |     |     |
| 21 | 112 | 591   | Maintenance of Structures                         | 0                   |      0           |     |     |     |
| 22 | 113 | 592   | Maintenance of Station Equipment                  | 8875.909999999916   |  -8875.91        |     |     |     |
| 23 | 114 | 593   | Maintenance of Overhead Lines                     | 1486616.5600000042  |     -1.48662e+06 |     |     |     |
| 24 | 115 | 594   | Maintenance of Underground Lines                  | -204369.70999999993 | 200870           |     |     |     |
| 25 | 116 | 595   | Maintenance of Line Transformers                  | 72.81               |    -72.81        |     |     |     |
| 26 | 117 | 596   | Maintenance of Street Lighting and Signal Systems | 1.66                |     -1.66        |     |     |     |
| 27 | 118 | 597   | Maintenance of Meters                             | 11223.1             | -11223.1         |     |     |     |
| 28 | 119 | 598   | Maintenance of Miscellaneous Distribution Plant   | -24600.59           |  24600.6         |     |     |     |
| 29 | 120 | Total |                                                   | [Target Cell]       |      2.59768e+07 |     |     |     |



min_row: 19
max_row: 29
min_col: 1
max_col: 8
target_cell_row_idx: 29
target_cell_col_idx: 4
target_cell_value: -27776696.200000007
formula: =SUM(D9:D28)
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        | F                 |
|---:|:----|:-------|:--------|:--------|:---------|:------------------|
|  1 |     |        |         |         |          |                   |
|  2 |     |        |         |         |          |                   |
|  3 |     |        |         |         |          |                   |
|  4 |     | Vin[V] | Iin[mA] | Vout[V] | Iout[mA] | Effcy[%]          |
|  5 |     | 24.01  | 42.4    | 3.304   | 250      | [Target Cell]     |
|  6 |     | 23.62  | 84      | 3.304   | 500      | 83.26277166243295 |
|  7 |     | 23.38  | 120.7   | 3.303   | 750      | 87.78454453384626 |
|  8 |     | 23.09  | 163     | 3.303   | 1000     | 87.7600852359532  |
|  9 |     | 23.99  | 197.3   | 3.303   | 1250     | 87.22907225873595 |
| 10 |     | 23.69  | 241.6   | 3.302   | 1500     | 86.53789706445562 |
| 11 |     | 23.78  | 284.2   | 3.301   | 1750     | 85.47668073928914 |
| 12 |     | 23.42  | 335.1   | 3.301   | 2010     | 84.54350779468305 |
| 13 |     |        |         |         |          |                   |
| 14 |     |        |         |         |          |                   |
| 15 |     |        |         |         |          |                   |



min_row: 1
max_row: 15
min_col: 1
max_col: 6
target_cell_row_idx: 5
target_cell_col_idx: 6
target_cell_value: 81.13757632433027
formula: =((D5*E5)/(B5*C5))*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       | E        | F                 |
|---:|:----|:-------|:--------|:--------|:---------|:------------------|
|  1 |     |        |         |         |          |                   |
|  2 |     |        |         |         |          |                   |
|  3 |     |        |         |         |          |                   |
|  4 |     | Vin[V] | Iin[mA] | Vout[V] | Iout[mA] | Effcy[%]          |
|  5 |     | 24.27  | 20.9    | 9.12    | 50.9     | [Target Cell]     |
|  6 |     | 24.14  | 41.4    | 9.1     | 101.4    | 92.32976717937635 |
|  7 |     | 23.86  | 81.8    | 9.08    | 201      | 93.51002281032183 |
|  8 |     | 24.01  | 120.2   | 9.06    | 300.5    | 94.33569346105789 |
|  9 |     | 23.75  | 159.7   | 9.05    | 398.2    | 95.01262235111889 |
| 10 |     | 24.02  | 195.3   | 9.05    | 500      | 96.45912925438053 |
| 11 |     | 23.69  | 240.8   | 9.06    | 600      | 95.29232093948832 |
| 12 |     | 24.09  | 273.6   | 9.05    | 700      | 96.11556565413812 |
| 13 |     | 23.8   | 315     | 9.05    | 790      | 95.36481259170337 |
| 14 |     | 23.99  | 316.8   | 9.05    | 800      | 95.26275678839248 |
| 15 |     | 23.66  | 361.2   | 9.06    | 890      | 94.35300196864215 |



min_row: 1
max_row: 15
min_col: 1
max_col: 6
target_cell_row_idx: 5
target_cell_col_idx: 6
target_cell_value: 91.51590066299585
formula: =((D5*E5)/(B5*C5))*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       | E        | F                 |
|---:|:----|:-------|:--------|:--------|:---------|:------------------|
| 14 |     |        |         |         |          |                   |
| 15 |     |        |         |         |          |                   |
| 16 |     |        |         |         |          |                   |
| 17 |     |        |         |         |          |                   |
| 18 |     |        |         |         |          |                   |
| 19 |     |        |         |         |          |                   |
| 20 |     |        |         |         |          |                   |
| 21 |     |        |         |         |          |                   |
| 22 |     |        |         |         |          |                   |
| 23 |     | Vin[V] | Iin[mA] | Vout[V] | Iout[mA] | Effcy[%]          |
| 24 |     | 12.02  | 78.1    | 3.305   | 250      | [Target Cell]     |
| 25 |     | 11.94  | 155.5   | 3.305   | 510      | 90.78349949102427 |
| 26 |     | 11.95  | 228.4   | 3.303   | 750      | 90.76237094138595 |
| 27 |     | 12     | 303.4   | 3.303   | 1000     | 90.72181938035597 |
| 28 |     | 12.05  | 380     | 3.303   | 1250     | 90.16706704520637 |
| 29 |     | 12.04  | 470     | 3.302   | 1500     | 87.52739096628261 |
| 30 |     | 12.02  | 560     | 3.302   | 1750     | 85.8465058236273  |
| 31 |     | 12.01  | 650     | 3.303   | 2020     | 85.468007429706   |
| 32 |     |        |         |         |          |                   |
| 33 |     |        |         |         |          |                   |
| 34 |     |        |         |         |          |                   |



min_row: 14
max_row: 34
min_col: 1
max_col: 6
target_cell_row_idx: 24
target_cell_col_idx: 6
target_cell_value: 88.0148536050671
formula: =((D24*E24)/(B24*C24))*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       | E        | F                 |
|---:|:----|:-------|:--------|:--------|:---------|:------------------|
|  1 |     |        |         |         |          |                   |
|  2 |     |        |         |         |          |                   |
|  3 |     |        |         |         |          |                   |
|  4 |     | Vin[V] | Iin[mA] | Vout[V] | Iout[mA] | Effcy[%]          |
|  5 |     | 24.46  | 21.84   | 9.12    | 51.5     | [Target Cell]     |
|  6 |     | 24.33  | 43.6    | 9.1     | 103.5    | 88.78776909241054 |
|  7 |     | 24.05  | 84.3    | 9.07    | 200.5    | 89.6972252844139  |
|  8 |     | 24.03  | 125.3   | 9.06    | 303.5    | 91.32339563574263 |
|  9 |     | 24.03  | 163.8   | 9.06    | 390      | 89.7687414541347  |
| 10 |     | 24.02  | 202.6   | 9.06    | 490      | 91.22457182357907 |
| 11 |     | 24.02  | 255.2   | 9.06    | 600      | 88.6800184798979  |
| 12 |     | 23.95  | 300     | 9.06    | 700      | 88.26722338204593 |
| 13 |     | 24.16  | 380.5   | 9.06    | 890      | 87.71353482260186 |
| 14 |     | 23.91  | 440     | 9.06    | 1010     | 86.97958252537927 |
| 15 |     |        |         |         |          |                   |



min_row: 1
max_row: 15
min_col: 1
max_col: 6
target_cell_row_idx: 5
target_cell_col_idx: 6
target_cell_value: 87.9210732031664
formula: =((D5*E5)/(B5*C5))*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       | E        | F                 |
|---:|:----|:-------|:--------|:--------|:---------|:------------------|
| 16 |     |        |         |         |          |                   |
| 17 |     |        |         |         |          |                   |
| 18 |     |        |         |         |          |                   |
| 19 |     |        |         |         |          |                   |
| 20 |     |        |         |         |          |                   |
| 21 |     |        |         |         |          |                   |
| 22 |     |        |         |         |          |                   |
| 23 |     |        |         |         |          |                   |
| 24 |     |        |         |         |          |                   |
| 25 |     | Vin[V] | Iin[mA] | Vout[V] | Iout[mA] | Effcy[%]          |
| 26 |     | 12.16  | 40      | 9.11    | 49.9     | [Target Cell]     |
| 27 |     | 12.15  | 80      | 9.1     | 98.8     | 92.49794238683127 |
| 28 |     | 12.12  | 170     | 9.06    | 209.4    | 92.0774606872452  |
| 29 |     | 12.11  | 250     | 9.06    | 300      | 89.77704376548307 |
| 30 |     | 12.11  | 330     | 9.06    | 390      | 88.41678552661213 |
| 31 |     | 12.1   | 420     | 9.07    | 490      | 87.45179063360882 |
| 32 |     | 12.07  | 580     | 9.14    | 610      | 79.6417449932863  |
| 33 |     | 12     | 670     | 9.12    | 700      | 79.40298507462686 |
| 34 |     | 12.06  | 760     | 9.09    | 800      | 79.3401413982718  |
| 35 |     | 12.06  | 850     | 9.05    | 900      | 79.4556628621598  |
| 36 |     | 12.02  | 960     | 8.99    | 1010     | 78.68743067110373 |



min_row: 16
max_row: 36
min_col: 1
max_col: 6
target_cell_row_idx: 26
target_cell_col_idx: 6
target_cell_value: 93.45990953947367
formula: =((D26*E26)/(B26*C26))*100