Triple
T15920271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red & Black Light |
E386074
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | track "Red & Black Light" |
E386074
|
NE FINISHED |
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: track "Red & Black Light" | Statement: [Red & Black Light, hasPart, track "Red & Black Light"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: track "Red & Black Light" Context triple: [Red & Black Light, hasPart, track "Red & Black Light"]
-
A.
track "Soul Dazzle"
"Soul Dazzle" is a song by American rapper U-God featured on his 2009 album *Dopium*.
-
B.
track "Black Tux, White Collar"
"Black Tux, White Collar" is a song featured on the album *Testing* by American rapper A$AP Rocky.
-
C.
Red & Black Light
chosen
Red & Black Light is a genre-blending jazz and electronic album by trumpeter Ibrahim Maalouf that explores modern, groove-driven soundscapes.
-
D.
track "Hood Boy"
"Hood Boy" is a song by American singer Fantasia from her self-titled second studio album, blending R&B and hip-hop influences.
-
E.
track "Lil' Lil'"
"Lil' Lil'" is a song featured on the hip hop album "Bridging the Gap" by Black Eyed Peas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15680c7b881909150f8b53bc058d4 |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5a96e508190a64c2be6dc506e86 |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:52 a.m.