Triple
T10262690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alien Superstar |
E240636
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Honey Dijon |
E853882
|
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: Honey Dijon | Statement: [Alien Superstar, producer, Honey Dijon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Honey Dijon Context triple: [Alien Superstar, producer, Honey Dijon]
-
A.
Honey Dijon
chosen
Honey Dijon is an acclaimed American DJ, producer, and trans rights advocate known for her influential work in house music and collaborations with major artists and fashion brands.
-
B.
Honey Chile
"Honey Chile" is a 1967 Motown soul single by Martha and the Vandellas that became one of the group's later charting hits.
-
C.
Doux
Doux is the sweetest style of Champagne, characterized by a high sugar content that gives it a rich, dessert-like taste.
-
D.
Saveur
Saveur is a culinary magazine known for its in-depth exploration of global cuisines, food culture, and travel.
-
E.
Sweeting
Sweeting is a surname most notably associated with Bahamian-born American former professional tennis player Ryan Sweeting.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d25dac34819099dbfad7f80507bb |
completed | April 7, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d74ff95bd08190975bc98c681caf07 |
completed | April 9, 2026, 7:06 a.m. |
Created at: April 6, 2026, 11:32 a.m.