Triple
T21633578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ludacris |
E533895
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | How Low (remix) |
—
|
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: How Low (remix) | Statement: [Ludacris, notableSong, How Low (remix)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: How Low (remix) Context triple: [Ludacris, notableSong, How Low (remix)]
-
A.
Down So Low
"Down So Low" is a soulful ballad best known from Linda Ronstadt’s 1976 album *Hasten Down the Wind*, originally written and recorded by singer-songwriter Tracy Nelson.
-
B.
How Low
chosen
"How Low" is a popular hip-hop single by American rapper Ludacris, known for its catchy hook and heavy club-oriented production.
-
C.
Lay Low
"Lay Low" is a popular West Coast hip hop track by Snoop Dogg featuring Nate Dogg, Master P, and others, known for its smooth G-funk production and laid-back gangsta rap vibe.
-
D.
Lay Low
Lay Low is a music album by French singer-songwriter and actress Lou Doillon, showcasing her introspective, folk-influenced style.
-
E.
L.O.V.E. (Remix)
"L.O.V.E. (Remix)" is a reworked version of the song "L.O.V.E." featured on the album "Elevation."
- 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef52185dbc819096ad2fc5b7d953f8 |
completed | April 27, 2026, 12:10 p.m. |
Created at: April 16, 2026, 6:35 p.m.