Task: Functional-Dependency (source dataset: Auto-Relate)

Given a table represented shown below, your task is to determine functional dependencies that exist in the table. Recall that a functional dependency is a relationship where the value of one attribute (or a set of attributes), known as the determinant columns, can uniquely determines the value of another attribute, known as the dependent columns (e.g., student-ID => student-Name, car-model => car-make, employee-ID => department, etc.).

Instructions:
Analyze the provided table below, identify all functional dependencies that should semantically hold in the table. Do not produce spurious relationships that not semantically meaningful.

No explanation, format the output as a JSON object:{"Functional-Dependency": <list of functional dependencies>}. Each functional dependency should be represented as [<determinant column>, <dependent column>]

Input Table:
| Date                    | Building   | Consumption type   |   Unit |   Year | Key             | City        | Country   |
|:------------------------|:-----------|:-------------------|-------:|-------:|:----------------|:------------|:----------|
| 2019-07-01 00:00:00.000 | B1006      | Water              | 466380 |   2019 | 2019Water       | Phoenix     | USA       |
| 2018-07-01 00:00:00.000 | B1002      | Water              | 288098 |   2018 | 2018Water       | New York    | USA       |
| 2018-11-01 00:00:00.000 | B1004      | Gas                |   6048 |   2018 | 2018Gas         | Chicago     | USA       |
| 2018-11-01 00:00:00.000 | B1006      | Water              | 292224 |   2018 | 2018Water       | Phoenix     | USA       |
| 2016-10-01 00:00:00.000 | B1000      | Water              | 334502 |   2016 | 2016Water       | New York    | USA       |
| 2019-08-01 00:00:00.000 | B1003      | Gas                |   5122 |   2019 | 2019Gas         | Los Angeles | USA       |
| 2016-06-01 00:00:00.000 | B1006      | Gas                |   3201 |   2016 | 2016Gas         | Phoenix     | USA       |
| 2016-10-01 00:00:00.000 | B1006      | Electricity        |  47578 |   2016 | 2016Electricity | Phoenix     | USA       |
| 2016-02-01 00:00:00.000 | B1003      | Electricity        |  30638 |   2016 | 2016Electricity | Los Angeles | USA       |
| 2018-04-01 00:00:00.000 | B1006      | Water              | 505586 |   2018 | 2018Water       | Phoenix     | USA       |
| 2018-11-01 00:00:00.000 | B1007      | Water              | 240399 |   2018 | 2018Water       | Chicago     | USA       |
| 2019-05-01 00:00:00.000 | B1005      | Gas                |   6909 |   2019 | 2019Gas         | Houston     | USA       |
| 2017-04-01 00:00:00.000 | B1003      | Water              | 483156 |   2017 | 2017Water       | Los Angeles | USA       |
| 2019-06-01 00:00:00.000 | B1000      | Electricity        |  38618 |   2019 | 2019Electricity | New York    | USA       |
| 2016-10-01 00:00:00.000 | B1004      | Electricity        |  42244 |   2016 | 2016Electricity | Chicago     | USA       |
| 2018-09-01 00:00:00.000 | B1002      | Water              | 343770 |   2018 | 2018Water       | New York    | USA       |
| 2018-12-01 00:00:00.000 | B1009      | Water              | 289432 |   2018 | 2018Water       | Los Angeles | USA       |
| 2017-03-01 00:00:00.000 | B1002      | Gas                |   4903 |   2017 | 2017Gas         | New York    | USA       |
| 2016-03-01 00:00:00.000 | B1007      | Water              | 461819 |   2016 | 2016Water       | Chicago     | USA       |
| 2016-03-01 00:00:00.000 | B1008      | Water              | 239402 |   2016 | 2016Water       | Chicago     | USA       |
| 2019-10-01 00:00:00.000 | B1002      | Gas                |   6194 |   2019 | 2019Gas         | New York    | USA       |
| 2017-02-01 00:00:00.000 | B1003      | Electricity        |  48384 |   2017 | 2017Electricity | Los Angeles | USA       |
| 2019-01-01 00:00:00.000 | B1004      | Electricity        |  33900 |   2019 | 2019Electricity | Chicago     | USA       |
| 2018-12-01 00:00:00.000 | B1005      | Electricity        |  35956 |   2018 | 2018Electricity | Houston     | USA       |
| 2018-10-01 00:00:00.000 | B1004      | Water              | 213170 |   2018 | 2018Water       | Chicago     | USA       |
| 2018-09-01 00:00:00.000 | B1006      | Gas                |   5682 |   2018 | 2018Gas         | Phoenix     | USA       |
| 2016-08-01 00:00:00.000 | B1004      | Electricity        |  39069 |   2016 | 2016Electricity | Chicago     | USA       |
| 2019-07-01 00:00:00.000 | B1002      | Electricity        |  50731 |   2019 | 2019Electricity | New York    | USA       |
| 2018-08-01 00:00:00.000 | B1001      | Water              | 287796 |   2018 | 2018Water       | New York    | USA       |
| 2018-06-01 00:00:00.000 | B1003      | Gas                |   4664 |   2018 | 2018Gas         | Los Angeles | USA       |
| 2016-08-01 00:00:00.000 | B1009      | Gas                |   3167 |   2016 | 2016Gas         | Los Angeles | USA       |
| 2017-10-01 00:00:00.000 | B1001      | Electricity        |  50511 |   2017 | 2017Electricity | New York    | USA       |
| 2017-11-01 00:00:00.000 | B1003      | Gas                |   3830 |   2017 | 2017Gas         | Los Angeles | USA       |
| 2018-09-01 00:00:00.000 | B1000      | Water              | 337972 |   2018 | 2018Water       | New York    | USA       |
| 2017-01-01 00:00:00.000 | B1001      | Electricity        |  38831 |   2017 | 2017Electricity | New York    | USA       |
| 2018-05-01 00:00:00.000 | B1006      | Electricity        |  32336 |   2018 | 2018Electricity | Phoenix     | USA       |
| 2019-04-01 00:00:00.000 | B1010      | Water              | 459811 |   2019 | 2019Water       | Los Angeles | USA       |
| 2017-12-01 00:00:00.000 | B1006      | Gas                |   3663 |   2017 | 2017Gas         | Phoenix     | USA       |
| 2016-04-01 00:00:00.000 | B1001      | Electricity        |  50193 |   2016 | 2016Electricity | New York    | USA       |
| 2016-03-01 00:00:00.000 | B1001      | Water              | 363959 |   2016 | 2016Water       | New York    | USA       |
| 2018-12-01 00:00:00.000 | B1004      | Electricity        |  39682 |   2018 | 2018Electricity | Chicago     | USA       |
| 2016-03-01 00:00:00.000 | B1010      | Water              | 471206 |   2016 | 2016Water       | Los Angeles | USA       |
| 2018-01-01 00:00:00.000 | B1002      | Gas                |   4910 |   2018 | 2018Gas         | New York    | USA       |
| 2018-04-01 00:00:00.000 | B1003      | Water              | 364306 |   2018 | 2018Water       | Los Angeles | USA       |
| 2018-11-01 00:00:00.000 | B1003      | Gas                |   3972 |   2018 | 2018Gas         | Los Angeles | USA       |
| 2017-11-01 00:00:00.000 | B1002      | Gas                |   4452 |   2017 | 2017Gas         | New York    | USA       |
| 2019-10-01 00:00:00.000 | B1007      | Electricity        |  40681 |   2019 | 2019Electricity | Chicago     | USA       |
| 2017-03-01 00:00:00.000 | B1008      | Water              | 501733 |   2017 | 2017Water       | Chicago     | USA       |
| 2018-11-01 00:00:00.000 | B1000      | Water              | 426014 |   2018 | 2018Water       | New York    | USA       |
| 2019-03-01 00:00:00.000 | B1002      | Water              | 404324 |   2019 | 2019Water       | New York    | USA       |



label: Building
City
Building
Country
output: {"Functional-Dependency": [["Building", "City"], ["Building", "Country"]]}
labeled_fds: Building
City
Building
Country
Unit
Date
Unit
Building
Unit
Year
Unit
Key
Unit
City
source: $MMTU_HOME/resources/Relationship-finding/FD/336330433