Made You Look
E501255
"Made You Look" is a 2022 doo-wop-influenced pop single by Meghan Trainor that became a viral hit, especially on TikTok, for its catchy hook and body-confidence message.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Made You Look canonical | 3 |
| Made You Look (A Cappella) | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T5193722 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Made You Look Context triple: [Meghan Trainor, notableWork, Made You Look]
-
A.
Look At You
"Look At You" is a pop song by American singer Rebecca Black, showcasing her more mature, contemporary sound following her viral debut with "Friday."
-
B.
Look at Me
"Look at Me" is a critically acclaimed novel by Jennifer Egan that explores identity, celebrity culture, and the impact of media in contemporary American life.
-
C.
Wanted You
"Wanted You" is a popular R&B-influenced hip-hop track by rapper Nav that helped raise his profile in the late 2010s.
-
D.
There You'll Be
"There You'll Be" is a power ballad by American country-pop singer Faith Hill, best known as the theme song from the 2001 film Pearl Harbor and one of her signature hits.
-
E.
I'm Not You
"I'm Not You" is a track from Clipse's debut album "Lord Willin'," showcasing the duo's gritty lyricism over Neptunes-produced beats.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Made You Look Target entity description: "Made You Look" is a 2022 doo-wop-influenced pop single by Meghan Trainor that became a viral hit, especially on TikTok, for its catchy hook and body-confidence message.
-
A.
Look At You
"Look At You" is a pop song by American singer Rebecca Black, showcasing her more mature, contemporary sound following her viral debut with "Friday."
-
B.
Look at Me
"Look at Me" is a critically acclaimed novel by Jennifer Egan that explores identity, celebrity culture, and the impact of media in contemporary American life.
-
C.
Wanted You
"Wanted You" is a popular R&B-influenced hip-hop track by rapper Nav that helped raise his profile in the late 2010s.
-
D.
There You'll Be
"There You'll Be" is a power ballad by American country-pop singer Faith Hill, best known as the theme song from the 2001 film Pearl Harbor and one of her signature hits.
-
E.
I'm Not You
"I'm Not You" is a track from Clipse's debut album "Lord Willin'," showcasing the duo's gritty lyricism over Neptunes-produced beats.
- F. None of above. chosen
Statements (48)
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Made You Look Description of subject: "Made You Look" is a 2022 doo-wop-influenced pop single by Meghan Trainor that became a viral hit, especially on TikTok, for its catchy hook and body-confidence message.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.