Triple
T19552394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brand X |
E489225
|
entity |
| Predicate | notableMember |
P10
|
FINISHED |
| Object | John Goodsall |
—
|
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: John Goodsall | Statement: [Brand X, notableMember, John Goodsall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Goodsall Context triple: [Brand X, notableMember, John Goodsall]
-
A.
John Goodsall
chosen
John Goodsall was a British-American guitarist best known as a founding member of the jazz-fusion band Brand X and for his innovative, technically skilled playing style.
-
B.
John Good
John Good is a former FBI agent best known for his key role in the ABSCAM undercover corruption investigation of the late 1970s and early 1980s.
-
C.
John Goodland
John Goodland is a notable individual associated with Grand Chute, Wisconsin, recognized for his significance to the local community.
-
D.
Joe Royall
Joe Royall is an individual recognized as a notable bearer of the surname Royall.
-
E.
Tony Gillingham
Tony Gillingham is a wealthy and charming aristocrat in Downton Abbey who becomes one of Lady Mary Crawley’s principal suitors.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d30a1d8819084d1bc60a5e49cae |
completed | April 20, 2026, 2:50 p.m. |
Created at: April 10, 2026, 1:41 p.m.