Triple
T18166687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wham! |
E434912
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Andrew Ridgeley |
—
|
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: Andrew Ridgeley | Statement: [Wham!, associatedAct, Andrew Ridgeley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Ridgeley Context triple: [Wham!, associatedAct, Andrew Ridgeley]
-
A.
Andrew Ridgeley
chosen
Andrew Ridgeley is an English musician and songwriter best known as one half of the 1980s pop duo Wham! alongside George Michael.
-
B.
Tony Hadley
Tony Hadley is an English pop singer best known as the lead vocalist of the 1980s new wave band Spandau Ballet.
-
C.
Gary Kemp
Gary Kemp is an English musician and actor best known as the guitarist and songwriter for the band Spandau Ballet and for his roles in films such as "The Krays."
-
D.
John Sykes
John Sykes is an English rock guitarist and songwriter best known for his work with bands like Thin Lizzy, Whitesnake, and Blue Murder.
-
E.
Mark Buckingham
Mark Buckingham is a British comic book artist best known for his long-running work on the acclaimed Vertigo series "Fables" and contributions to numerous DC and Marvel titles.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec7e41c8190bd19dc5f62c69608 |
completed | April 19, 2026, 1:55 p.m. |
Created at: April 10, 2026, 10:30 a.m.