Triple
T23241508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loud Pipes |
E581459
|
entity |
| Predicate | featuredArtist |
P997
|
FINISHED |
| Object | Juvenile |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Juvenile | Statement: [Loud Pipes, featuredArtist, Juvenile]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juvenile Context triple: [Loud Pipes, featuredArtist, Juvenile]
-
A.
Juvenile
chosen
Juvenile is an American rapper from New Orleans best known as a member of the Hot Boys and for his influential late-1990s Southern hip hop hits like "Back That Azz Up."
-
B.
Junior
Junior is the protagonist of the novel "Love" by Toni Morrison, around whom the story’s complex relationships and themes of desire, memory, and power revolve.
-
C.
Junior
Junior is a 1994 comedy film in which Arnold Schwarzenegger plays a scientist who becomes pregnant as part of an experimental fertility project.
-
D.
Junior
Junior is a professional Colombian football club based in Barranquilla, known for its strong fan base and multiple national league titles.
-
E.
Junior
Junior is a musician best known for performing the song "Look What Love Has Done."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e2460556f88190be1744a84a84173f |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192edd974819093a57456e7b12a03 |
completed | April 29, 2026, 5:11 a.m. |
Created at: April 17, 2026, 4:10 p.m.