Triple
T10555475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romeo Crennel |
E249071
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Crennel |
E249071
|
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: Crennel | Statement: [Romeo Crennel, familyName, Crennel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crennel Context triple: [Romeo Crennel, familyName, Crennel]
-
A.
Crennel
chosen
Crennel is the surname of Romeo Crennel, an American football coach best known for his roles as an NFL head coach and defensive coordinator.
-
B.
Dungy
Dungy is the surname of Tony Dungy, a former NFL head coach and Super Bowl champion known for his leadership and advocacy on and off the field.
-
C.
Griese
Griese is a surname most prominently associated with Bob Griese, the Hall of Fame American football quarterback.
-
D.
Coryell
Coryell is the named defendant in the landmark 1823 U.S. case Corfield v. Coryell, which helped define the scope of the Privileges and Immunities Clause.
-
E.
Dilfer
Dilfer is the surname of former NFL quarterback and Super Bowl champion Trent Dilfer.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d52712a9988190bf63e7c47f6e6fc1 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9346f6a38819087647e7a09f40c41 |
completed | April 10, 2026, 5:33 p.m. |
Created at: April 6, 2026, 12:34 p.m.