Triple
T3367064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucky Daye |
E70861
|
entity |
| Predicate | hasDiscographyEntry |
P1995
|
FINISHED |
| Object | Candydrip |
E352611
|
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: Candydrip | Statement: [Lucky Daye, hasDiscographyEntry, Candydrip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Candydrip Context triple: [Lucky Daye, hasDiscographyEntry, Candydrip]
-
A.
Candydrip
chosen
Candydrip is a 2022 R&B album by American singer-songwriter Lucky Daye, known for its lush production and sensual, futuristic soul sound.
-
B.
Candy Shop
"Candy Shop" is a 2005 hip hop single by 50 Cent featuring Olivia, produced by Scott Storch, known for its seductive lyrics and catchy, club-oriented beat.
-
C.
Candy Ferocity
Candy Ferocity is a fictional main character known for her bold, flamboyant persona and striking, high-energy presence.
-
D.
The Drop
The Drop is a crime drama novel by Dennis Lehane that follows a lonely bartender entangled in a dangerous scheme involving mob money, a stray dog, and a mysterious woman in working-class Brooklyn.
-
E.
Sugar on a Stick
Sugar on a Stick is a portable, USB-based distribution of the Sugar learning environment designed to provide children with an easy, bootable educational platform.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2890480819082fe2e3c2874cece |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3545ea1b08190ad84b7e5f70b4d2e |
completed | March 13, 2026, 12:03 a.m. |
Created at: March 8, 2026, 3:13 p.m.