MMTU-benchmark/MMTU huggingface dataset:
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                              | Artist_Name   | Album_Name                            | Genre                                                      | Price   | CopyRight                                                                                                                         | Time   | Released   |
|:---------------------------------------|:--------------|:--------------------------------------|:-----------------------------------------------------------|:--------|:----------------------------------------------------------------------------------------------------------------------------------|:-------|:-----------|
| Turn Around ( 5,4,3,2,1 ) [ AK Remix ] | Flo Rida      | Turn Around ( 5,4,3,2,1 ) [ Remixes ] | Dance,Music,Hip-Hop / Rap , Dirty South , Rap , Electronic | $ 1.29  | 2011 Atlantic Recording Corporation for the United States and WEA International Inc. for the world outside of the United States . | 5:09   | 19-Apr-11  |

Entity B:
| Song_Name                        | Artist_Name   | Album_Name               | Genre              | Price   | CopyRight                                                                           | Time   | Released           |
|:---------------------------------|:--------------|:-------------------------|:-------------------|:--------|:------------------------------------------------------------------------------------|:-------|:-------------------|
| Good Feeling ( Jaywalker Remix ) | Flo Rida      | Good Feeling ( Remixes ) | Dance & Electronic | $ 1.29  | ( C ) 2009 MPL Tours Inc. under exclusive license to StarCon LLC d/b/a Hear MusicTM | 4:51   | November 15 , 2011 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 3554
rtable_id: 19790
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                                  | Artist_Name   | Album_Name   | Genre                                                     | Price   | CopyRight                                                                                                                       | Time   | Released   |
|:-------------------------------------------|:--------------|:-------------|:----------------------------------------------------------|:--------|:--------------------------------------------------------------------------------------------------------------------------------|:-------|:-----------|
| Medicated ( feat . Chevy Woods & Juicy J ) | Wiz Khalifa   | O.N.I.F.C.   | Hip-Hop/Rap , Music , Hardcore Rap , East Coast Rap , Rap | $ 1.29  | 2012 Atlantic Recording Corporation for the United States and WEA International Inc. for the world outside of the United States | 5:30   | 4-Dec-12   |

Entity B:
| Song_Name                                      | Artist_Name   | Album_Name              | Genre         | Price   | CopyRight                                                                                                                       | Time   | Released          |
|:-----------------------------------------------|:--------------|:------------------------|:--------------|:--------|:--------------------------------------------------------------------------------------------------------------------------------|:-------|:------------------|
| Initiation ( feat . Lola Monroe ) [ Explicit ] | Wiz Khalifa   | O.N.I.F.C. [ Explicit ] | Rap & Hip-Hop | $ 1.29  | 2012 Atlantic Recording Corporation for the United States and WEA International Inc. for the world outside of the United States | 4:29   | December 4 , 2012 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 3443
rtable_id: 34350
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name          | Artist_Name   | Album_Name    | Genre               | Price   | CopyRight            | Time   | Released   |
|:-------------------|:--------------|:--------------|:--------------------|:--------|:---------------------|:-------|:-----------|
| Extra Extra Credit | Wiz Khalifa   | Flight School | Hip-Hop/Rap , Music | $ 0.99  | 2009 Rostrum Records | 4:03   | 17-Apr-09  |

Entity B:
| Song_Name                       | Artist_Name   | Album_Name                 | Genre         | Price   | CopyRight       | Time   | Released        |
|:--------------------------------|:--------------|:---------------------------|:--------------|:--------|:----------------|:-------|:----------------|
| Extra Extra Credit [ Explicit ] | Wiz Khalifa   | Flight School [ Explicit ] | Rap & Hip-Hop | $ 0.99  | 2013 Mad Decent | 4:03   | April 17 , 2009 |



entityA: entityA.csv
entityB: entityB.csv
label: 1
original: ltable_id: 3354
rtable_id: 17643
label: 1
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name               | Artist_Name   | Album_Name   | Genre                                          | Price   | CopyRight                            | Time   | Released   |
|:------------------------|:--------------|:-------------|:-----------------------------------------------|:--------|:-------------------------------------|:-------|:-----------|
| VHS Outro ( Interlude ) | X Ambassadors | VHS          | Alternative , Music , Rock , Adult Alternative | $ 1.29  | 2015 KIDinaKORNER/Interscope Records | 1:25   | 30-Jun-15  |

Entity B:
| Song_Name                | Artist_Name   | Album_Name       | Genre            | Price   | CopyRight                                  | Time   | Released       |
|:-------------------------|:--------------|:-----------------|:-----------------|:--------|:-------------------------------------------|:-------|:---------------|
| First Show ( Interlude ) | X Ambassadors | VHS [ Explicit ] | Alternative Rock | $ 1.29  | ( C ) 2015 KIDinaKORNER/Interscope Records | 0:11   | June 30 , 2015 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 249
rtable_id: 53074
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                                                             | Artist_Name   | Album_Name                | Genre                                                  | Price   | CopyRight                                                                                                                                                                                  | Time   | Released   |
|:----------------------------------------------------------------------|:--------------|:--------------------------|:-------------------------------------------------------|:--------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------|:-----------|
| Dangerous ( feat . Sam Martin ) [ Robin Schulz Remix ] [ Radio Edit ] | David Guetta  | Listen ( Deluxe Version ) | Dance , Music , Rock , House , Electronic , French Pop | $ 1.29  | 2014 What A Music Ltd. under exclusive license to Parlophone/Warner Music France , under exclusive license to Atlantic Recording Corporation for the United States . All rights reserved . | 3:20   | 24-Nov-14  |

Entity B:
| Song_Name                                                   | Artist_Name   | Album_Name        | Genre              | Price   | CopyRight                | Time   | Released           |
|:------------------------------------------------------------|:--------------|:------------------|:-------------------|:--------|:-------------------------|:-------|:-------------------|
| Lift me up ( feat . Nico & Vinz , Ladysmith Black Mambazo ) | David Guetta  | Listen ( Deluxe ) | Dance & Electronic | $ 1.29  | 2015 If Moving Your Mine | 3:58   | November 24 , 2014 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 1301
rtable_id: 27982
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name               | Artist_Name   | Album_Name   | Genre                     | Price      | CopyRight                              | Time   | Released   |
|:------------------------|:--------------|:-------------|:--------------------------|:-----------|:---------------------------------------|:-------|:-----------|
| Rewind ( feat . Monty ) | Fetty Wap     | Fetty Wap    | Hip-Hop/Rap , Music , Rap | Album Only | 2015 300 Entertainment/RGF Productions | 5:36   |            |

Entity B:
| Song_Name                       | Artist_Name   | Album_Name          | Genre         | Price   | CopyRight                                                                           | Time   | Released            |
|:--------------------------------|:--------------|:--------------------|:--------------|:--------|:------------------------------------------------------------------------------------|:-------|:--------------------|
| Jugg ( feat . Monty ) [ Clean ] | Fetty Wap     | Fetty Wap [ Clean ] | Rap & Hip-Hop | $ 1.29  | ( C ) 2000 Mute Records Ltd. , a BMG Company , under exclusive license to INgrooves | 3:20   | September 25 , 2015 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 2734
rtable_id: 17185
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name   | Artist_Name   | Album_Name      | Genre                                                      | Price   | CopyRight                        | Time   | Released   |
|:------------|:--------------|:----------------|:-----------------------------------------------------------|:--------|:---------------------------------|:-------|:-----------|
| X2CU        | Jason Derulo  | Everything Is 4 | Pop , Music , Rock , R&B / Soul , Contemporary R&B , Dance | $ 1.29  | 2015 Warner Bros. . Records Inc. | 5:13   | 1-Jun-15   |

Entity B:
| Song_Name   | Artist_Name   | Album_Name                | Genre   | Price   | CopyRight          | Time   | Released      |
|:------------|:--------------|:--------------------------|:--------|:--------|:-------------------|:-------|:--------------|
| X2CU        | Jason Derulo  | Everything Is 4 [ Clean ] | Pop     | $ 1.29  | 2011 Because Music | 5:14   | June 1 , 2015 |



entityA: entityA.csv
entityB: entityB.csv
label: 1
original: ltable_id: 3926
rtable_id: 16397
label: 1
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name         | Artist_Name   | Album_Name        | Genre                                            | Price   | CopyRight                                                                         | Time   | Released   |
|:------------------|:--------------|:------------------|:-------------------------------------------------|:--------|:----------------------------------------------------------------------------------|:-------|:-----------|
| Better Than Words | One Direction | Midnight Memories | Pop , Music , Rock , Pop/Rock , Teen Pop , Dance | $ 1.29  | 2013 Simco Limited under exclusive license to Sony Music Entertainment UK Limited | 3:27   | 25-Nov-13  |

Entity B:
| Song_Name         | Artist_Name   | Album_Name                   | Genre   | Price   | CopyRight                            | Time   | Released           |
|:------------------|:--------------|:-----------------------------|:--------|:--------|:-------------------------------------|:-------|:-------------------|
| Better Than Words | One Direction | Midnight Memories ( Deluxe ) | Pop     | $ 1.29  | ( C ) 2014 Disney Enterprises , Inc. | 3:28   | November 25 , 2013 |



entityA: entityA.csv
entityB: entityB.csv
label: 1
original: ltable_id: 4468
rtable_id: 31072
label: 1
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
|   Song_Name | Artist_Name   | Album_Name      | Genre                                  | Price   | CopyRight                                                                                                                  | Time   | Released   |
|------------:|:--------------|:----------------|:---------------------------------------|:--------|:---------------------------------------------------------------------------------------------------------------------------|:-------|:-----------|
|          45 | Shinedown     | Leave a Whisper | Rock , Music , Hard Rock , Alternative | $ 1.29  | 2003 Atlantic Recording Corporation for the United States and WEA International for the world outside of the United States | 4:09   | 27-May-03  |

Entity B:
|   Song_Name | Artist_Name   | Album_Name      | Genre   | Price   | CopyRight       | Time   | Released      |
|------------:|:--------------|:----------------|:--------|:--------|:----------------|:-------|:--------------|
|          45 | Shinedown     | Leave A Whisper | Rock    | $ 1.29  | 2015 Mad Decent | 4:09   | May 27 , 2003 |



entityA: entityA.csv
entityB: entityB.csv
label: 1
original: ltable_id: 1636
rtable_id: 27530
label: 1
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                    | Artist_Name   | Album_Name   | Genre                                                  | Price   | CopyRight                                                                                                                                                                                | Time   | Released   |
|:-----------------------------|:--------------|:-------------|:-------------------------------------------------------|:--------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------|:-----------|
| The Whisperer ( feat . Sia ) | David Guetta  | Listen       | Dance , Music , Electronic , House , Rock , French Pop | $ 1.29  | 2014 What A Music Ltd. under exclusive license to Parlophone/Warner Music France , under exclusive license to Atlantic Recording Corporation for the United States . All rights reserved | 3:54   | 24-Nov-14  |

Entity B:
| Song_Name                     | Artist_Name   | Album_Name   | Genre              | Price   | CopyRight                | Time   | Released           |
|:------------------------------|:--------------|:-------------|:-------------------|:--------|:-------------------------|:-------|:-------------------|
| Listen ( feat . John Legend ) | David Guetta  | Listen       | Dance & Electronic | $ 1.29  | 2015 If Moving Your Mine | 3:46   | November 24 , 2014 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 1194
rtable_id: 28049
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                                                     | Artist_Name   | Album_Name                  | Genre         | Price   | CopyRight                                               | Time   | Released   |
|:--------------------------------------------------------------|:--------------|:----------------------------|:--------------|:--------|:--------------------------------------------------------|:-------|:-----------|
| Toyfriend ( feat . Wynter Gordon ) [ Continuous Mix Version ] | David Guetta  | One Love ( Deluxe Version ) | Dance , Music | $ 1.29  | 2010 Gum Prod licence exclusive Parlophone Music France | 2:51   | 21-Aug-09  |

Entity B:
| Song_Name                                   | Artist_Name   | Album_Name                  | Genre              | Price   | CopyRight                                                                                         | Time   | Released         |
|:--------------------------------------------|:--------------|:----------------------------|:-------------------|:--------|:--------------------------------------------------------------------------------------------------|:-------|:-----------------|
| Sound Of Letting Go ( Feat . Chris Willis ) | David Guetta  | One Love ( Deluxe Version ) | Dance & Electronic | $ 1.29  | ( C ) 2014 Swedish House Mafia Holdings Ltd ( BVI ) under exclusive license to Virgin Records Ltd | 3:47   | August 21 , 2009 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 1268
rtable_id: 34910
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                       | Artist_Name   | Album_Name                   | Genre               | Price   | CopyRight                         | Time   | Released   |
|:--------------------------------|:--------------|:-----------------------------|:--------------------|:--------|:----------------------------------|:-------|:-----------|
| Crew Love ( feat . The Weeknd ) | Drake         | Take Care ( Deluxe Version ) | Hip-Hop/Rap , Music | $ 1.29  | ‰ ãÑ 2011 Cash Money Records Inc. | 3:28   | 15-Nov-11  |

Entity B:
| Song_Name                               | Artist_Name   | Album_Name                                   | Genre         | Price   | CopyRight                          | Time   | Released            |
|:----------------------------------------|:--------------|:---------------------------------------------|:--------------|:--------|:-----------------------------------|:-------|:--------------------|
| All Me [ feat . 2 Chainz ] [ Explicit ] | Drake         | Nothing Was The Same ( Deluxe ) [ Explicit ] | Rap & Hip-Hop | $ 1.29  | ( C ) 2013 Cash Money Records Inc. | 4:30   | September 24 , 2013 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 5146
rtable_id: 34093
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                                                      | Artist_Name   | Album_Name                                           | Genre                                   | Price   | CopyRight                                | Time   | Released   |
|:---------------------------------------------------------------|:--------------|:-----------------------------------------------------|:----------------------------------------|:--------|:-----------------------------------------|:-------|:-----------|
| We 'll Be Coming Back ( feat . Example ) [ Jacob Plant Remix ] | Calvin Harris | We 'll Be Coming Back ( feat . Example ) [ Remixes ] | Dance , Music , R&B / Soul , Electronic | $ 1.29  | 2013 Sony Music Entertainment UK Limited | 5:02   | 5-Feb-13   |

Entity B:
| Song_Name                                  | Artist_Name               | Album_Name                        | Genre              | Price   | CopyRight                                                                    | Time   | Released        |
|:-------------------------------------------|:--------------------------|:----------------------------------|:-------------------|:--------|:-----------------------------------------------------------------------------|:-------|:----------------|
| How Deep Is Your Love ( Chris Lake Remix ) | Calvin Harris & Disciples | How Deep Is Your Love ( Remixes ) | Dance & Electronic | $ 1.29  | ( C ) 2015 Island Records , a division of Universal Music Operations Limited | 5:06   | August 7 , 2015 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 3017
rtable_id: 22499
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                | Artist_Name   | Album_Name           | Genre                     | Price      | CopyRight                              | Time   | Released   |
|:-------------------------|:--------------|:---------------------|:--------------------------|:-----------|:---------------------------------------|:-------|:-----------|
| Whateva ( feat . Monty ) | Fetty Wap     | Fetty Wap ( Deluxe ) | Hip-Hop/Rap , Music , Rap | Album Only | 2015 300 Entertainment/RGF Productions | 5:11   |            |

Entity B:
| Song_Name                             | Artist_Name   | Album_Name                        | Genre         | Price   | CopyRight                                                                           | Time   | Released            |
|:--------------------------------------|:--------------|:----------------------------------|:--------------|:--------|:------------------------------------------------------------------------------------|:-------|:--------------------|
| Whateva ( feat . Monty ) [ Explicit ] | Fetty Wap     | Fetty Wap ( Deluxe ) [ Explicit ] | Rap & Hip-Hop | $ 1.29  | ( C ) 2000 Mute Records Ltd. , a BMG Company , under exclusive license to INgrooves | 5:11   | September 25 , 2015 |



entityA: entityA.csv
entityB: entityB.csv
label: 1
original: ltable_id: 2742
rtable_id: 17181
label: 1
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                                                     | Artist_Name   | Album_Name                  | Genre         | Price   | CopyRight                                               | Time   | Released   |
|:--------------------------------------------------------------|:--------------|:----------------------------|:--------------|:--------|:--------------------------------------------------------|:-------|:-----------|
| Toyfriend ( feat . Wynter Gordon ) [ Continuous Mix Version ] | David Guetta  | One Love ( Deluxe Version ) | Dance , Music | $ 1.29  | 2010 Gum Prod licence exclusive Parlophone Music France | 2:51   | 21-Aug-09  |

Entity B:
| Song_Name                                                                   | Artist_Name   | Album_Name                  | Genre              | Price   | CopyRight                                                                                         | Time   | Released         |
|:----------------------------------------------------------------------------|:--------------|:----------------------------|:-------------------|:--------|:--------------------------------------------------------------------------------------------------|:-------|:-----------------|
| On The Dancefloor ( Feat . Will I Am & Apl De Ap ; Continuous Mix Version ) | David Guetta  | One Love ( Deluxe Version ) | Dance & Electronic | $ 1.29  | ( C ) 2014 Swedish House Mafia Holdings Ltd ( BVI ) under exclusive license to Virgin Records Ltd | 4:16   | August 21 , 2009 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 1263
rtable_id: 34892
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name      | Artist_Name   | Album_Name                    | Genre                                                                       | Price   | CopyRight                                                                                                                                                                                                                                                              | Time   | Released   |
|:---------------|:--------------|:------------------------------|:----------------------------------------------------------------------------|:--------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------|:-----------|
| You Gon na Fly | Keith Urban   | Get Closer ( Deluxe Version ) | Country , Music , Honky Tonk , Pop , Pop/Rock , Contemporary Country , Rock | $ 1.29  | ‰ ãÑ 2010 Hit Red Records under exclusive license to Capitol Records Nashville . All rights reserved . Unauthorized reproduction is a violation of applicable laws . Manufactured by Capitol Records Nashville , 3322 West End Avenue , 11th Floor , Nashville , TN 37 | 3:36   | 22-Feb-11  |

Entity B:
| Song_Name      | Artist_Name   | Album_Name                    | Genre   | Price   | CopyRight                                                                       | Time   | Released           |
|:---------------|:--------------|:------------------------------|:--------|:--------|:--------------------------------------------------------------------------------|:-------|:-------------------|
| You Gon na Fly | Keith Urban   | Get Closer ( Deluxe Version ) | Country | $ 1.29  | ( C ) 2011 Hit Red Records under exclusive license to Capitol Records Nashville | 3:36   | February 22 , 2011 |



entityA: entityA.csv
entityB: entityB.csv
label: 1
original: ltable_id: 5885
rtable_id: 19151
label: 1
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name               | Artist_Name   | Album_Name   | Genre                                          | Price   | CopyRight                            | Time   | Released   |
|:------------------------|:--------------|:-------------|:-----------------------------------------------|:--------|:-------------------------------------|:-------|:-----------|
| VHS Outro ( Interlude ) | X Ambassadors | VHS          | Alternative , Music , Rock , Adult Alternative | $ 1.29  | 2015 KIDinaKORNER/Interscope Records | 1:25   | 30-Jun-15  |

Entity B:
| Song_Name                               | Artist_Name   | Album_Name    | Genre            | Price   | CopyRight                                  | Time   | Released       |
|:----------------------------------------|:--------------|:--------------|:-----------------|:--------|:-------------------------------------------|:-------|:---------------|
| Adam & Noah 's Priorities ( Interlude ) | X Ambassadors | VHS [ Clean ] | Alternative Rock | $ 1.29  | ( C ) 2015 KIDinaKORNER/Interscope Records | 0:27   | June 30 , 2015 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 275
rtable_id: 52959
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                | Artist_Name   | Album_Name           | Genre                     | Price      | CopyRight                              | Time   | Released   |
|:-------------------------|:--------------|:---------------------|:--------------------------|:-----------|:---------------------------------------|:-------|:-----------|
| Whateva ( feat . Monty ) | Fetty Wap     | Fetty Wap ( Deluxe ) | Hip-Hop/Rap , Music , Rap | Album Only | 2015 300 Entertainment/RGF Productions | 5:11   |            |

Entity B:
| Song_Name                              | Artist_Name   | Album_Name                     | Genre         | Price   | CopyRight                                                                           | Time   | Released            |
|:---------------------------------------|:--------------|:-------------------------------|:--------------|:--------|:------------------------------------------------------------------------------------|:-------|:--------------------|
| For My Team ( feat . Monty ) [ Clean ] | Fetty Wap     | Fetty Wap ( Deluxe ) [ Clean ] | Rap & Hip-Hop | $ 1.29  | ( C ) 2000 Mute Records Ltd. , a BMG Company , under exclusive license to INgrooves | 3:28   | September 25 , 2015 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 2696
rtable_id: 17160
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                                                  | Artist_Name   | Album_Name           | Genre                                     | Price   | CopyRight                                                         | Time   | Released   |
|:-----------------------------------------------------------|:--------------|:---------------------|:------------------------------------------|:--------|:------------------------------------------------------------------|:-------|:-----------|
| I 'm a Machine ( feat . Crystal Nicole and Tyrese Gibson ) | David Guetta  | Nothing But the Beat | Dance , Music , Rock , House , Electronic | $ 1.29  | 2011 What A Music Ltd , Licence exclusive Parlophone Music France | 3:34   | 26-Aug-11  |

Entity B:
| Song_Name                                     | Artist_Name   | Album_Name           | Genre              | Price   | CopyRight            | Time   | Released         |
|:----------------------------------------------|:--------------|:---------------------|:-------------------|:--------|:---------------------|:-------|:-----------------|
| Night Of Your Life ( Feat . Jennifer Hudson ) | David Guetta  | Nothing But The Beat | Dance & Electronic | $ 1.29  | 2009 Andy Henningsen | 3:42   | August 26 , 2011 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 1292
rtable_id: 34023
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                            | Artist_Name   |   Album_Name | Genre                                                                                       | Price   | CopyRight                    | Time   | Released   |
|:-------------------------------------|:--------------|-------------:|:--------------------------------------------------------------------------------------------|:--------|:-----------------------------|:-------|:-----------|
| Goodbye to You ( feat . Dot Rotten ) | Ed Sheeran    |            5 | Pop , Music , Rock , Singer/Songwriter , Contemporary Singer/Songwriter , Adult Alternative | $ 1.29  | 2014 Warner Music UK LImited | 5:30   | 23-Jun-14  |

Entity B:
| Song_Name       | Artist_Name   |   Album_Name | Genre   | Price   | CopyRight          | Time   | Released       |
|:----------------|:--------------|-------------:|:--------|:--------|:-------------------|:-------|:---------------|
| You ( + Wiley ) | Ed Sheeran    |            5 | Pop     | $ 1.29  | Dub Police Records | 3:21   | June 23 , 2014 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 470
rtable_id: 1872
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                    | Artist_Name   | Album_Name   | Genre                                                  | Price   | CopyRight                                                                                                                                                                                | Time   | Released   |
|:-----------------------------|:--------------|:-------------|:-------------------------------------------------------|:--------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------|:-----------|
| The Whisperer ( feat . Sia ) | David Guetta  | Listen       | Dance , Music , Electronic , House , Rock , French Pop | $ 1.29  | 2014 What A Music Ltd. under exclusive license to Parlophone/Warner Music France , under exclusive license to Atlantic Recording Corporation for the United States . All rights reserved | 3:54   | 24-Nov-14  |

Entity B:
| Song_Name                                               | Artist_Name   | Album_Name        | Genre              | Price   | CopyRight                | Time   | Released           |
|:--------------------------------------------------------|:--------------|:------------------|:-------------------|:--------|:-------------------------|:-------|:-------------------|
| Hey Mama ( feat . Nicki Minaj , Bebe Rexha & Afrojack ) | David Guetta  | Listen ( Deluxe ) | Dance & Electronic | $ 1.29  | 2015 If Moving Your Mine | 3:12   | November 24 , 2014 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 1226
rtable_id: 28022
label: 0
Task: Entity-Matching (source dataset: iTunes-Amazon)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| Song_Name                     | Artist_Name   | Album_Name                  | Genre       | Price   | CopyRight                           | Time   | Released   |
|:------------------------------|:--------------|:----------------------------|:------------|:--------|:------------------------------------|:-------|:-----------|
| Bad Blood ( Karaoke Version ) | Taylor Swift  | Taylor Swift Karaoke : 1989 | Pop , Music | $ 1.29  | ‰ ãÑ 2014 Big Machine Records , LLC | 3:29   | 3-Mar-15   |

Entity B:
| Song_Name   | Artist_Name   |   Album_Name | Genre   | Price   | CopyRight                              | Time   | Released          |
|:------------|:--------------|-------------:|:--------|:--------|:---------------------------------------|:-------|:------------------|
| Bad Blood   | Taylor Swift  |         1989 | Pop     | $ 1.29  | ( C ) 2014 Big Machine Records , LLC . | 3:31   | October 27 , 2014 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 6621
rtable_id: 784
label: 0
Task: Entity-Matching (source dataset: Fodors-Zagats)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| name     | addr            | city              | phone         | type   |   class |
|:---------|:----------------|:------------------|:--------------|:-------|--------:|
| fringale | ' 570 4th st. ' | ` san francisco ' | 415/543 -0573 | french |     101 |

Entity B:
| name     | addr               | city              | phone        | type              |   class |
|:---------|:-------------------|:------------------|:-------------|:------------------|--------:|
| fringale | ' 570 fourth st. ' | ` san francisco ' | 415-543-0573 | ` french bistro ' |     101 |



entityA: entityA.csv
entityB: entityB.csv
label: 1
original: ltable_id: 101
rtable_id: 319
label: 1
Task: Entity-Matching (source dataset: Fodors-Zagats)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| name     | addr                   | city    | phone         | type          |   class |
|:---------|:-----------------------|:--------|:--------------|:--------------|--------:|
| bistango | ' 1100 peachtree st. ' | atlanta | 404/724 -0901 | mediterranean |     386 |

Entity B:
| name                              | addr                  | city    | phone        | type                 |   class |
|:----------------------------------|:----------------------|:--------|:-------------|:---------------------|--------:|
| ` ritz-carlton cafe ( atlanta ) ' | ' 181 peachtree st. ' | atlanta | 404-659-0400 | ` american ( new ) ' |     711 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 386
rtable_id: 330
label: 0
Task: Entity-Matching (source dataset: Fodors-Zagats)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| name                   | addr        | city            | phone         | type     |   class |
|:-----------------------|:------------|:----------------|:--------------|:---------|--------:|
| ` pacific dining car ' | ' 6th st. ' | ` los angeles ' | 213/483 -6000 | american |     153 |

Entity B:
| name       | addr            | city              | phone        | type       |   class |
|:-----------|:----------------|:------------------|:-------------|:-----------|--------:|
| ` tu lan ' | ' 8 sixth st. ' | ` san francisco ' | 415-626-0927 | vietnamese |     750 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 156
rtable_id: 215
label: 0
Task: Entity-Matching (source dataset: Fodors-Zagats)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| name        | addr                  | city            | phone         | type   |   class |
|:------------|:----------------------|:----------------|:--------------|:-------|--------:|
| ` le dome ' | ' 8720 sunset blvd. ' | ` los angeles ' | 310/659 -6919 | french |     145 |

Entity B:
| name                      | addr                  | city             | phone        | type        |   class |
|:--------------------------|:----------------------|:-----------------|:-------------|:------------|--------:|
| ` spago ( los angeles ) ' | ' 8795 sunset blvd. ' | ` w. hollywood ' | 310-652-4025 | californian |      20 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 148
rtable_id: 238
label: 0
Task: Entity-Matching (source dataset: Fodors-Zagats)

You are given two data records from two datasets that may refer to the same real-world entity. Each record consists of multiple attributes, such as name, address, and other identifying details. Your goal is to determine whether pairs of records refer to the same entity (match) or different entities (non-match).

No explanation and return the final answer as a JSON object, {"label": "<LABEL>"}, where "<LABEL>" is either "match" or "non-match".

Entity A:
| name        | addr                  | city            | phone         | type   |   class |
|:------------|:----------------------|:----------------|:--------------|:-------|--------:|
| ` le dome ' | ' 8720 sunset blvd. ' | ` los angeles ' | 310/659 -6919 | french |     145 |

Entity B:
| name          | addr                  | city             | phone        | type             |   class |
|:--------------|:----------------------|:-----------------|:-------------|:-----------------|--------:|
| ` duke \ 's ' | ' 8909 sunset blvd. ' | ` w. hollywood ' | 310-652-3100 | ` coffee shops ' |     551 |



entityA: entityA.csv
entityB: entityB.csv
label: 0
original: ltable_id: 148
rtable_id: 17
label: 0