MMTU-benchmark/MMTU huggingface dataset:
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source           |
|:-----------------|
| USS Bremerton    |
| USS America      |
| USS Newport News |
| USS Squall       |
| USS Whirlwind    |

Eample Output Column:
| target      |
|:------------|
| Los Angeles |
| America     |
| Los Angeles |
| Cyclone     |
| Cyclone     |

Test Input Column:
| source              |
|:--------------------|
| USS Abraham Lincoln |
| USS Alabama         |
| USS Alaska          |
| USS Albany          |
| USS Albuquerque     |
| USS Alexandria      |
| USS Anchorage       |
| USS Annapolis       |
| USS Antietam        |
| USS Anzio           |



label: Nimitz
Ohio
Ohio
Los Angeles
Los Angeles
Los Angeles
San Antonio
Los Angeles
Ticonderoga
Ticonderoga
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source            |
|:------------------|
| Benjamin Harrison |
| Warren G. Harding |
| Gerald R. Ford    |
| Richard M. Nixon  |
| Abraham Lincoln   |

Eample Output Column:
| target                                              |
|:----------------------------------------------------|
| Caroline Lavinia Scott Harrison; Mary Lord Harrison |
| Florence Kling Harding                              |
| Betty Ford                                          |
| Pat Nixon                                           |
| Mary Todd Lincoln                                   |

Test Input Column:
| source            |
|:------------------|
| George Washington |
| John Adams        |
| James Madison     |
| John Quincy Adams |
| Andrew Jackson    |
| Martin Van Buren  |
| Millard Fillmore  |
| Franklin Pierce   |
| Andrew Johnson    |
| Ulysses S. Grant  |



label: Martha Washington
Abigail Adams
Dolley Madison
Louisa Catherine Adams
Rachel Jackson
Hannah Hoes Van Buren
Abigail Powers Fillmore
Jane M. Pierce
Eliza McCardle Johnson
Julia Dent Grant
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source         |
|:---------------|
| Sam Bradford   |
| Earl Campbell  |
| Carson Palmer  |
| Jameis Winston |
| Gary Beban     |

Eample Output Column:
| target              |
|:--------------------|
| Oklahoma            |
| Texas               |
| Southern California |
| Florida State       |
| UCLA                |

Test Input Column:
| source             |
|:-------------------|
| Robert Griffin III |
| Cameron Newton     |
| Mark Ingram        |
| Tim Tebow          |
| Troy Smith         |
| Reggie Bush        |
| Matt Leinart       |
| Jason White        |
| Eric Crouch        |
| Chris Weinke       |



label: Baylor
Auburn
Alabama
Florida
Ohio State
Southern California
Southern California
Oklahoma
Nebraska
Florida State
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                               |
|:-------------------------------------|
| Bob Hope Airport                     |
| Pittsburgh International Airport     |
| Albuquerque International Sunport    |
| Indianapolis International Airport   |
| Raleigh-Durham International Airport |

Eample Output Column:
| target   |
|:---------|
| CA       |
| PA       |
| NM       |
| IN       |
| NC       |

Test Input Column:
| source                                            |
|:--------------------------------------------------|
| Lambert–St. Louis International Airport           |
| William P. Hobby Airport                          |
| Nashville International Airport                   |
| Austin-Bergstrom International Airport            |
| Kansas City International Airport                 |
| Metropolitan Oakland International Airport        |
| Louis Armstrong New Orleans International Airport |
| John Wayne Airport                                |
| Cleveland Hopkins International Airport           |
| San Jose International Airport                    |



label: MO
TX
TN
TX
MO
CA
LA
CA
OH
CA
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                      |
|:----------------------------|
| With a Smile and a Song     |
| Fathoms Below               |
| Friends on the Other Side   |
| I Wanna Be Like Other Girls |
| So This is Love             |

Eample Output Column:
| target                         |
|:-------------------------------|
| Snow White                     |
| The Little Mermaid and Sequels |
| The Princess and the Frog      |
| Mulan and Sequel               |
| Cinderella and Sequels         |

Test Input Column:
| source                         |
|:-------------------------------|
| Princess almost there          |
| Down in New Orleans (Prologue) |
| Down in New Orleans            |
| Almost There                   |
| When We're Human               |
| Gonna Take You There           |
| Ma Belle Evangeline            |
| Dig a Little Deeper            |
| Down in New Orleans (Reprise)  |
| Daughters of Triton            |



label: The Princess and the Frog
The Princess and the Frog
The Princess and the Frog
The Princess and the Frog
The Princess and the Frog
The Princess and the Frog
The Princess and the Frog
The Princess and the Frog
The Princess and the Frog
The Little Mermaid and Sequels
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source       |
|:-------------|
| Indianapolis |
| Columbia     |
| Santa Fe     |
| Richmond     |
| Baton Rouge  |

Eample Output Column:
| target         |
|:---------------|
| Indiana        |
| South Carolina |
| New Mexico     |
| Virginia       |
| Louisiana      |

Test Input Column:
| source      |
|:------------|
| Montgomery  |
| Juneau      |
| Phoenix     |
| Little Rock |
| Sacramento  |
| Denver      |
| Hartford    |
| Dover       |
| Tallahassee |
| Atlanta     |



label: Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                  |
|:------------------------|
| Imperial Theatre        |
| Ethel Barrymore Theatre |
| Belasco Theatre         |
| New Amsterdam Theatre   |
| Vivian Beaumont Theatre |

Eample Output Column:
| target                          |
|:--------------------------------|
| Shubert Organization            |
| Shubert Organization            |
| Shubert Organization            |
| Disney; Theatrical; Productions |
| Lincoln Center Theater          |

Test Input Column:
| source                         |
|:-------------------------------|
| Al Hirschfeld Theatre          |
| Ambassador Theatre             |
| American Airlines Theatre      |
| August Wilson Theatre          |
| Bernard B Jacobs Theatre       |
| Booth Theatre                  |
| Broadhurst Theatre             |
| Broadway Theatre               |
| Brooks Atkinson Theatre        |
| Cadillac Winter Garden Theatre |



label: Jujamcyn Theaters
Shubert Organization
Roundabout Theatre; Company
Jujamcyn Theaters
Shubert Organization
Shubert Organization
Shubert Organization
Shubert Organization
Nederlander Organization
Shubert Organization
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source         |
|:---------------|
| Indiana        |
| South Carolina |
| New Mexico     |
| Virginia       |
| Louisiana      |

Eample Output Column:
| target   |
|:---------|
| IN       |
| SC       |
| NM       |
| VA       |
| LA       |

Test Input Column:
| source      |
|:------------|
| Alabama     |
| Alaska      |
| Arizona     |
| Arkansas    |
| California  |
| Colorado    |
| Connecticut |
| Delaware    |
| Florida     |
| Georgia     |



label: AL
AK
AZ
AR
CA
CO
CT
DE
FL
GA
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source            |
|:------------------|
| Millard Fillmore  |
| Abraham Lincoln   |
| Benjamin Harrison |
| Woodrow Wilson    |
| Thomas Jefferson  |

Eample Output Column:
| target   |
|:---------|
| New York |
| Kentucky |
| Ohio     |
| Virginia |
| Virginia |

Test Input Column:
| source                 |
|:-----------------------|
| Zachary Taylor         |
| Warren G. Harding      |
| John Quincy Adams      |
| John F. Kennedy        |
| Grover Cleveland       |
| William Henry Harrison |
| John Tyler             |
| William Howard Taft    |
| James Buchanan         |
| Rutherford B. Hayes    |



label: Virginia
Ohio
Massachusetts
Massachusetts
New Jersey
Virginia
Virginia
Ohio
Pennsylvania
Ohio
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                |
|:----------------------|
| Copper (II) sulfate   |
| Nitrogen (II) oxide   |
| Magnesium Sulfate     |
| Copper (II) Hydroxide |
| Calcium Chromate      |

Eample Output Column:
| target   |
|:---------|
| CuSO4    |
| NO       |
| MgSO4    |
| Cu(OH)2  |
| CaCrO4   |

Test Input Column:
| source            |
|:------------------|
| Ammonia           |
| Carbon dioxide    |
| Carbon monoxide   |
| Chlorine          |
| Hydrogen chloride |
| Hydrogen          |
| Hydrogen sulfide  |
| Methane           |
| Nitrogen          |
| Oxygen            |



label: NH3
CO2
CO
Cl2
HCl
H2
H2S
CH4
N2
O2
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                    |
|:--------------------------|
| Karolinska Institute      |
| Seoul National University |
| Monash University         |
| Johns Hopkins University  |
| Brown University          |

Eample Output Column:
| target             |
|:-------------------|
| Sweden             |
| Korea, Republic Of |
| Australia          |
| US                 |
| US                 |

Test Input Column:
| source                                |
|:--------------------------------------|
| Harvard University                    |
| Massachusetts Institute of Technology |
| University of Cambridge               |
| University of Oxford                  |
| University of California, Berkeley    |
| Stanford University                   |
| Princeton University                  |
| University of California, Los Angeles |
| University of Tokyo                   |
| Yale University                       |



label: US
US
UK
UK
US
US
US
US
Japan
US
Task: semantic-transform (source dataset: SEMA-join)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                            |
|:----------------------------------|
| Arkansas Baptist College          |
| Puerto Rico Conservatory of Music |
| Wheeling Jesuit University        |
| Eastern University                |
| Roberts Wesleyan College          |

Eample Output Column:
| target        |
|:--------------|
| Arkansas      |
| Puerto Rico   |
| West Virginia |
| Pennsylvania  |
| New York      |

Test Input Column:
| source                                  |
|:----------------------------------------|
| AIB College of Business                 |
| Abilene Christian University            |
| Abraham Baldwin Agricultural College    |
| Academy of Art University               |
| Adams State University                  |
| Adelphi University                      |
| Adrian College                          |
| Adventist University of Health Sciences |
| Agnes Scott College                     |
| Alabama State University                |



label: Iowa
Texas
Georgia
California
Colorado
New York
Michigan
Florida
Georgia
Alabama
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source   |
|:---------|
| pei      |
| cle      |
| crv      |
| rez      |
| rgl      |

Eample Output Column:
| target       |
|:-------------|
| pereira      |
| cleveland    |
| crotone      |
| resende rj   |
| rio gallegos |

Test Input Column:
| source   |
|:---------|
| het      |
| ctg      |
| gbe      |
| boi      |
| kif      |
| lci      |
| esf      |
| aex      |
| jej      |
| lle      |



label: hohhot
cartagena
gaborone
boise id
kingfisher l ont. on
laconia nh
alexandria la
alexandria la
jeh
malelane
transformation: source-airport code->target-city
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/AirportcodeToCity
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source   |
|:---------|
| gva      |
| mxp      |
| tlh      |
| bcn      |
| sto      |

Eample Output Column:
| target        |
|:--------------|
| Switzerland   |
| Italy         |
| United States |
| Spain         |
| Sweden        |

Test Input Column:
| source   |
|:---------|
| lax      |
| ptj      |
| mth      |
| agc      |
| hrl      |
| mgc      |
| lfk      |
| sjc      |
| cho      |
| aza      |



label: United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
transformation: source-lit->target-United States
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/airportToCountry
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source      |
|:------------|
| Flycatchers |
| Cormorants  |
| Salamanders |
| Cormorants  |
| Grebes      |

Eample Output Column:
| target             |
|:-------------------|
| Eastern Phoebe     |
| Pelagic Cormorant  |
| Spotted Salamander |
| Great Cormorant    |
| Clark's Grebe      |

Test Input Column:
| source                 |
|:-----------------------|
| Albatross              |
| Anhingas               |
| Barn Owls              |
| Chickadees and Titmice |
| Chickadees and Titmice |
| Cormorants             |
| Cormorants             |
| Cormorants             |
| Cormorants             |
| Cranes                 |



label: Laysan Albatross
Anhinga
Barn Owl
Black-Capped Chickadee
Carolina Chickadee
Double-Crested Cormorant
Neotropic Cormorant
Cormorant
Red-Faced Cormorant
Sandhill Crane
transformation: source-Frogs->target-Frog
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/AnimalToGenusSpeciesCommonNames
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source        |
|:--------------|
| Kenya         |
| Kenya         |
| Ethiopia      |
| Jamaica       |
| United States |

Eample Output Column:
| target          |
|:----------------|
| Silas Kiplagat  |
| William Yiampoy |
| Abera Kuma      |
| Yohan Blake     |
| Ben Blankenship |

Test Input Column:
| source        |
|:--------------|
| United States |
| United States |
| Kenya         |
| United States |
| Mexico        |
| United States |
| United States |
| United States |
| Kenya         |
| Kenya         |



label: Andrew Valmon
Aries Merritt
Asbel Kiprop
Ashton Eaton
Bernardo Segura
Brandon Johnson
Brycen Spratling
Butch Reynolds
Collins Cheboi
Daniel Komen
transformation: source-Country->target-Athlete
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/AthletesHoldingWorldRecordsPerCountry
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                                   |
|:-----------------------------------------|
| BANCA CRED.COOPER.VICENTINO POJANA MAGG. |
| AS DNB NORD BANKA                        |
| DANSKE BANK A/SLATVIJA BRANCH            |
| OKASAN SECURITIES CO. LTD.               |
| LYXOR ASSET MANAGEMENT                   |

Eample Output Column:
| target   |
|:---------|
| ITALY    |
| LATVIA   |
| LATVIA   |
| JAPAN    |
| FRANCE   |

Test Input Column:
| source                                 |
|:---------------------------------------|
| BANKE MILLIE AFGHAN                    |
| DA AFGHANISTAN BANK                    |
| BRAC AFGHANISTAN BANK                  |
| NATIONAL BANK OF PAKISTAN KABUL BRANCH |
| MAIWAND BANK                           |
| GHAZANFAR BANK                         |
| PASHTANY BANK                          |
| BAKHTAR BANK                           |
| AFGHANISTAN INTERNATIONAL BANK         |
| FIRST MICROFINANCE BANK LTD. THE       |



label: AFGHANISTAN
AFGHANISTAN
AFGHANISTAN
AFGHANISTAN
AFGHANISTAN
AFGHANISTAN
AFGHANISTAN
AFGHANISTAN
AFGHANISTAN
AFGHANISTAN
transformation: source-AUSTRALIA AND NEW ZEALAND BANKING GROUP LIMITED->target-#NAME?
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/bankToCountryDistinct
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source          |
|:----------------|
| White Hart Lane |
| Olimpico        |
| Stade Vélodrome |
| Rajko Mitic     |
| Luigi Ferraris  |

Eample Output Column:
| target                 |
|:-----------------------|
| Tottenham Hotspur F.C. |
| S.S. Lazio             |
| Olympique de Marseille |
| Red Star Belgrade      |
| U.C. Sampdoria         |

Test Input Column:
| source                                      |
|:--------------------------------------------|
| Anfield                                     |
| Bentegodi                                   |
| Camp Nou                                    |
| Campo de Futbol de Vallecas                 |
| Constant Vanden Stock Stadium               |
| Emirates Stadium                            |
| Estadio Monumental Antonio Vespucio Liberti |
| Etihad Stadium                              |
| Luigi Ferraris                              |
| Juventus Stadium                            |



label: Liverpool F.C.
A.C. Chievo Verona
F.C. Barcelona
Rayo Vallecano
R.S.C. Anderlecht
Arsenal F.C.
Club Atletico River Plate
Manchester City F.C.
Genoa C.F.C.
Juventus F.C.
transformation: source-arena->target-club
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/ArenaTocurrentSoccerClubs
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                                       |
|:---------------------------------------------|
| SUEZ CANAL BANK                              |
| CHANG HWA COMMERCIAL BANK LTD.  TOKYO BRANCH |
| CENTRAL BANK OF EGYPT CAIRO                  |
| BANKHAUS ERBE                                |
| SUEZ CANAL BANK                              |

Eample Output Column:
| target      |
|:------------|
| SUCAEGCXMAN |
| CCBCJPJTXXX |
| CBEGEGCAALX |
| WBCCRUMMXXX |
| SUCAEGCXGIZ |

Test Input Column:
| source                                |
|:--------------------------------------|
| ALWATANY BANK OF EGYPT                |
| CHELYABINVESTBANK                     |
| ARAB BANK PLC                         |
| BANQUE EXTERIEURE D'ALGERIE           |
| CREDIT COOPERATIF                     |
| NATIONAL BANK FOR DEVELOPMENT         |
| CITADEL INVESTMENT GROUP  L.L.C.      |
| FIDUCIARY TRUST COMPANY INTERNATIONAL |
| AMERICAN BUSINESS BANK                |
| BANQUE EXTERIEURE D'ALGERIE           |



label: WABAEGCXMOH
CHINRU4CXXX
ARABQAQARD3
BEXADZAL073
CCOPFRPPFXD
NBDEEGCXGZI
CITGUS44CTC
FCNYUS33TMS
ACBBUS6LXXX
BEXADZAL053
transformation: source-bank->target-swiftcode
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/BankToSwiftCode
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source               |
|:---------------------|
| Thomas Pynchon       |
| John Steinbeck       |
| John Steinbeck       |
| Thomas Pynchon       |
| David Foster Wallace |

Eample Output Column:
| target                                      |
|:--------------------------------------------|
| Gravity's Rainbow                           |
| Sweet Thursday                              |
| The Short Reign of Pippin IV: A Fabrication |
| The Crying of Lot 49                        |
| The Pale King                               |

Test Input Column:
| source           |
|:-----------------|
| Jonathan Franzen |
| Jonathan Franzen |
| Jonathan Franzen |
| Jonathan Franzen |
| J. D. Salinger   |
| J. D. Salinger   |
| Ernest Hemingway |
| Ernest Hemingway |
| Ernest Hemingway |
| Ernest Hemingway |



label: The Twenty-Seventh City
Strong Motion
The Corrections
Freedom
The Catcher in the Rye
Franny and Zooey
The Torrents of Spring
The Sun Also Rises
A Farewell to Arms
To Have and Have Not
transformation: source-Author->target-Novel
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/Author2Novels
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                                                 |
|:-------------------------------------------------------|
| PHAROS SECURITIES                                      |
| GDF SUEZ                                               |
| BANK OF ALEXANDRIA S A E                               |
| BELTONE SECURITIES BROKERAGE S.A.E                     |
| PRINCIPAL BANK FOR DEVELOPMENT AND AGRICULTURAL CREDIT |

Eample Output Column:
| target   |
|:---------|
| CAIRO    |
| PARIS    |
| CAIRO    |
| CAIRO    |
| CAIRO    |

Test Input Column:
| source                                                   |
|:---------------------------------------------------------|
| COMMERCIAL BANK -LANTA-BANK'                             |
| GENERAL ELECTRIC COMPANY                                 |
| THE 77 BANKLTD.                                          |
| MIZUHO CORPORATE BANK LTD. PARIS BRANCH                  |
| LA BANQUE POSTALE                                        |
| BANQUE D'ESCOMPTE                                        |
| ALWATANY BANK OF EGYPT                                   |
| NATIONAL BANK OF KUWAIT (INTERNATIONAL) PLC PARIS BRANCH |
| GALLIARD CAPITAL MANAGEMENT INC                          |
| SUEZ CANAL BANK                                          |



label: MOSCOW
STAMFORDCT
SENDAI
PARIS
CHALONS EN CHAMPAGNE
PARIS
EL MANSOURA
PARIS
MINNEAPOLISMN
6TH OF OCTOBER
transformation: source-bank->target-city
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/BankToCity
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source        |
|:--------------|
| Busan         |
| Dubai         |
| Nanchang      |
| Kuala Lumpur  |
| New York City |

Eample Output Column:
| target                                     |
|:-------------------------------------------|
| We've the Zenith Tower A                   |
| Almas Tower                                |
| Jiangxi Nanchang Greenland Central Plaza 1 |
| Petronas Tower 2                           |
| One57                                      |

Test Input Column:
| source        |
|:--------------|
| New York City |
| New York City |
| Chicago       |
| Chicago       |
| Chicago       |
| Houston       |
| Houston       |
| Los Angeles   |
| Chicago       |
| Hong Kong     |



label: Chrysler Building
Empire State Building
John Hancock Center
Aon Center
Willis Tower
JPMorgan Chase Tower
Wells Fargo Plaza
U.S. Bank Tower
Franklin Center
Bank of China Tower
transformation: source-City->target-Building
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/City2TallBuildings
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source          |
|:----------------|
| Nokia           |
| IBM             |
| Bank of America |
| Oracle          |
| Starbucks       |

Eample Output Column:
| target            |
|:------------------|
| Rajeev Suri       |
| Ginni Rometty     |
| Brian T. Moynihan |
| Larry Ellison     |
| Howard Schultz    |

Test Input Column:
| source    |
|:----------|
| Microsoft |
| GM        |
| GE        |
| Staples   |
| Dell      |



label: Satya Nadella
Mary T. Barra
Jeffrey R. Immelt
Ron Sargent
Michael S. Dell
transformation: source-Company->target-Ceo
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/CompanyToCeo
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source      |
|:------------|
| Rotterdam   |
| Toulouse    |
| Geneva      |
| Marseille   |
| Los Angeles |

Eample Output Column:
| target        |
|:--------------|
| Netherlands   |
| France        |
| Switzerland   |
| France        |
| United States |

Test Input Column:
| source     |
|:-----------|
| Toronto    |
| Istanbul   |
| Aarhus     |
| Munich     |
| Barcelona  |
| Alexandria |
| Krakow     |
| Graz       |
| Osaka      |
| Reykjavik  |



label: Canada
Turkey
Denmark
Germany
Spain
Egypt
Poland
Austria
Japan
Iceland
transformation: source-City->target-Country
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/CityToCountry
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source                 |
|:-----------------------|
| Microsoft Corporation  |
| Google Inc             |
| General Motors Company |
| Amazon.com Inc.        |
| Apple Inc              |

Eample Output Column:
| target       |
|:-------------|
| BBG00009KTG6 |
| BBG0013YWBF3 |
| BBG009KHTL39 |
| BBG00094DJF9 |
| BBG004HSPP80 |

Test Input Column:
| source                          |
|:--------------------------------|
| International Business Machines |
| Bank of America Corporation     |
| General Electric Company        |
| Comcast Corporation             |
| SAP AG                          |



label: BBG0000WHK50
BBG00000YH03
BBG0000112Y3
BBG00001KTF4
BBG000BR9Q00
transformation: source-Company name->target-BBG ID
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/CompanyToBloombergID
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source   |
|:---------|
| {        |
| (        |
| 2        |
| #        |
| +        |

Eample Output Column:
|   target |
|---------:|
|      123 |
|       40 |
|       50 |
|       35 |
|       43 |

Test Input Column:
| source   |
|:---------|
| 3        |
| C        |
| L        |
| x        |



label: 51
67
76
120
transformation: source-Char->target-Ascii
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/AsciiToUnicode
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source          |
|:----------------|
| Nokia           |
| IBM             |
| Bank of America |
| Oracle          |
| Starbucks       |

Eample Output Column:
| target             |
|:-------------------|
| Telecommunications |
| IT Hardware        |
| Finance            |
| IT Software        |
| Coffee shop        |

Test Input Column:
| source    |
|:----------|
| Microsoft |
| GM        |
| GE        |
| Staples   |
| Dell      |



label: IT Software
Automobile
Electricity
office supply chain
IT Services
transformation: source-Company->target-Industry
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/CompanyToIndustry
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source        |
|:--------------|
| GRAYMONT      |
| BELLEFONTAINE |
| Kansas        |
| Fort Bidwell  |
| SOUTH BEND    |

Eample Output Column:
|   target |
|---------:|
|    61743 |
|    39737 |
|    61933 |
|    96112 |
|    68058 |

Test Input Column:
| source          |
|:----------------|
| LA MIRADA       |
| West Point      |
| La Mirada       |
| WESTTOWN        |
| NINDE           |
| Boston          |
| La Mirada       |
| Boston          |
| Warwick         |
| Washingtonville |



label: 90638
10997
90639
10998
22526
2108
90637
2109
10990
10992
transformation: source-city->target-zip code
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/CityToZIp
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source    |
|:----------|
| 2x-Platin |
| Platin    |
| Platin    |
| Gold      |
| Gold      |

Eample Output Column:
| target              |
|:--------------------|
| Guns N' Roses       |
| Wildecker Herzbuben |
| Def Leppard         |
| Bruce Springsteen   |
| Eric Clapton        |

Test Input Column:
| source    |
|:----------|
| 2x-Platin |
| Gold      |
| Platin    |
| Gold      |
| Gold      |
| 2x-Platin |
| Gold      |
| Gold      |
| Platin    |
| Gold      |



label: Abba
Abba
Abba
AC/DC
AC/DC
AC/DC
Barbelivien & Anais
Barclay James Harvest
Bee Gees
Berger & France Gall
transformation: source-award->target-artist
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/AwardToArtist
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source     |
|:-----------|
| Cobalt     |
| Cesium     |
| Cerium     |
| Gadolinium |
| Argon      |

Eample Output Column:
|   target |
|---------:|
|     2870 |
|      678 |
|     3257 |
|     3233 |
|     -186 |

Test Input Column:
| source    |
|:----------|
| Actinium  |
| Aluminum  |
| Americium |
| Antimony  |
| Arsenic   |
| Astatine  |
| Barium    |
| Beryllium |
| Bismuth   |
| Boron     |



label: 3200
2467
2607
1750
613
337
1140
2970
1560
2550
transformation: source-element->target-B.P.
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/ElementToBP
Task: semantic-transform (source dataset: DataXFormer)

Your task is to perform semantic data transformation on a given column of input values. You will first be shown a pair of example input/output columns, to learn the desired semantic transformations as demonstrated by the input/output columns. Then you will be given a new input column, where the goal is to generate output values corresponding to each value in the new input column, following the same transformation relationship demonstrated in the example input/output columns. 

No explanation is needed, and do not generate code. Simply return your answer in JSON format: {"output": [<output column>]}.

Eample Input Column:

| source             |
|:-------------------|
| Alain Prost        |
| Jim Clark          |
| Alain Prost        |
| Fernando Alonso    |
| Juan Manuel Fangio |

Eample Output Column:
|   target |
|---------:|
|     1989 |
|     1965 |
|     1986 |
|     2006 |
|     1956 |

Test Input Column:
| source             |
|:-------------------|
| Michael Schumacher |
| Juan Manuel Fangio |
| Alain Prost        |
| Sebastian Vettel   |
| Jack Brabham       |
| Jackie Stewart     |
| Niki Lauda         |
| Nelson Piquet      |
| Ayrton Senna       |
| Alberto Ascari     |



label: 1994
1951
1985
2010
1959
1969
1975
1981
1988
1952
transformation: source-Driver->target-Year
source: $MMTU_HOME/data/semantic-transform/sample1000/DataXFormer/Driver2Champioships