Task: header-value-matching (source dataset: TableGPT)

Given the input table data and the list of candidate headers, please determine the most suitable column header for each column in the table. Please only choose column headers from the candidate list. Please only return the most suitable column header for each column. Return the chosen column headers in a list. Do not return the entire table. No explanation and return your answer in JSON format: {"column_headers": "<a list of headers for each column chosen from the candidate list>"}.

Table Data:
| Col_0     | Col_1           |   Col_2 |   Col_3 |   Col_4 |   Col_5 |   Col_6 |   Col_7 |   Col_8 |   Col_9 |   Col_10 |   Col_11 |   Col_12 |   Col_13 |   Col_14 |   Col_15 |   Col_16 |   Col_17 |   Col_18 |
|:----------|:----------------|--------:|--------:|--------:|--------:|--------:|--------:|--------:|--------:|---------:|---------:|---------:|---------:|---------:|---------:|---------:|---------:|---------:|
| TIGR00090 | rsfS_iojap_ybeB |      99 |   57.89 |    6.32 |   35.79 |   63.87 |    7.56 |   28.57 |   73.17 |     6.67 |    20.17 |    76.99 |     4.25 |    18.76 |    86.75 |     1.09 |    12.15 |    89.7  |
| TIGR00396 | leuS_bact       |     843 |   51.04 |    6.25 |   42.71 |   61.81 |    6.69 |   31.5  |   73.75 |     4.86 |    21.4  |    79.57 |     3.36 |    17.07 |    91.22 |     0.72 |     8.06 |    96.92 |
| TIGR00095 | TIGR00095       |     194 |   51.06 |    7.45 |   41.49 |   57.5  |    6.25 |   36.25 |   68.25 |     5.89 |    25.86 |    74.43 |     4.08 |    21.48 |    87.03 |     1.23 |    11.74 |    94.73 |
| TIGR00250 | RNAse_H_YqgF    |     130 |   44.83 |    8.05 |   47.13 |   49.56 |    9.65 |   40.79 |   68.46 |     5.39 |    26.14 |    73.97 |     3.76 |    22.27 |    86.49 |     1.05 |    12.46 |    91.87 |
| TIGR00064 | ftsY            |     279 |   60.49 |   11.11 |   28.4  |   70.7  |    9.3  |   20    |   79.42 |     7.22 |    13.36 |    81.57 |     4.49 |    13.94 |    90.26 |     1.02 |     8.71 |    93.56 |

Candidate column headers:
Monophyletic (Phylum %)
Monophyletic (Order %)
Operationally  monophyletic (Family %)
Monophyletic (Family %)
Operationally  monophyletic (Phylum %)
Operationally  monophyletic (Class %)
Polyphyletic (Class %)
Length (bp)
Gene ID
Polyphyletic (Genus %)
Monophyletic (Genus %)
Polyphyletic (Order %)
Polyphyletic (Family %)
Operationally  monophyletic (Order %)
Polyphyletic (Phylum %)
Monophyletic (Species %)
Operationally  monophyletic (Genus %)
Monophyletic (Class %)
Name



headers: Monophyletic (Phylum %)
Monophyletic (Order %)
Operationally  monophyletic (Family %)
Monophyletic (Family %)
Operationally  monophyletic (Phylum %)
Operationally  monophyletic (Class %)
Polyphyletic (Class %)
Length (bp)
Gene ID
Polyphyletic (Genus %)
Monophyletic (Genus %)
Polyphyletic (Order %)
Polyphyletic (Family %)
Operationally  monophyletic (Order %)
Polyphyletic (Phylum %)
Monophyletic (Species %)
Operationally  monophyletic (Genus %)
Monophyletic (Class %)
Name
label: Gene ID
Name
Length (bp)
Monophyletic (Phylum %)
Operationally  monophyletic (Phylum %)
Polyphyletic (Phylum %)
Monophyletic (Class %)
Operationally  monophyletic (Class %)
Polyphyletic (Class %)
Monophyletic (Order %)
Operationally  monophyletic (Order %)
Polyphyletic (Order %)
Monophyletic (Family %)
Operationally  monophyletic (Family %)
Polyphyletic (Family %)
Monophyletic (Genus %)
Operationally  monophyletic (Genus %)
Polyphyletic (Genus %)
Monophyletic (Species %)