Triple
T21010534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot & Wet |
E517535
|
entity |
| Predicate | hasPerformerMember |
P46749
|
FINISHED |
| Object | Quinnes "Q" Parker |
—
|
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: Quinnes "Q" Parker | Statement: [Hot & Wet, hasPerformerMember, Quinnes "Q" Parker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quinnes "Q" Parker Context triple: [Hot & Wet, hasPerformerMember, Quinnes "Q" Parker]
-
A.
Quinnes "Q" Parker
chosen
Quinnes "Q" Parker is an American R&B singer best known as a member of the Grammy-winning group 112.
-
B.
Jay Parker
Jay Parker is a fictional character portrayed by actor Josh Stamberg, best known from his role in the television series "Drop Dead Diva."
-
C.
Brad Parker
Brad Parker is a screenwriter known for collaborating with Carey Van Dyke on film and television projects.
-
D.
Jack Parker
Jack Parker is a legendary American college ice hockey coach best known for his long, highly successful tenure leading Boston University’s men’s hockey program to multiple national championships.
-
E.
Phil Packer
Phil Packer is a British former army officer and charity campaigner known for his remarkable fundraising endurance challenges undertaken after sustaining severe spinal injuries.
- 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_69e0b50192308190a284fcc89dd23a49 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc3fdf3c8190abd3db7f5eb503a0 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:53 p.m.