Triple
T22987832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grant Strong |
E571961
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Grant Strong |
—
|
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: Grant Strong | Statement: [Grant Strong, name, Grant Strong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grant Strong Context triple: [Grant Strong, name, Grant Strong]
-
A.
Grant Strong
chosen
Grant Strong is an individual notable enough to be recognized as a bearer of the Strong surname.
-
B.
Andrew Strong
Andrew Strong is an Irish singer and actor best known for his powerful soul vocals and breakout role in the film adaptation of "The Commitments."
-
C.
Dale Strong
Dale Strong is an American Republican politician serving as the U.S. Representative for Alabama’s 5th congressional district.
-
D.
Richard Strong
Richard Strong is a landscape architect known for his work on the design of Toronto’s prominent civic plaza, Nathan Phillips Square.
-
E.
Ed Strong
Ed Strong is a theatrical producer best known for his work on the hit jukebox musical "Jersey Boys."
- 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1829b4ea88190bc1a01183df7a1bb |
completed | April 29, 2026, 4:01 a.m. |
Created at: April 17, 2026, 3:49 p.m.