Triple
T11180754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Griese |
E264530
|
entity |
| Predicate | Bob Griese |
P97705
|
FINISHED |
| Object | instanceOf Pro Football Hall of Fame quarterback |
—
|
LITERAL 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: instanceOf Pro Football Hall of Fame quarterback | Statement: [Brian Griese, Bob Griese, instanceOf Pro Football Hall of Fame quarterback]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Bob Griese Context triple: [Brian Griese, Bob Griese, instanceOf Pro Football Hall of Fame quarterback]
-
A.
Brian Griese
Indicates that Brian Griese is the subject or agent involved in the specified relationship or action.
-
B.
notableFormerQuarterback
Indicates that the subject was previously a quarterback and is recognized as notable or distinguished in that former role.
-
C.
SeattleQuarterback
Indicates that an entity serves as the quarterback for a football team based in Seattle.
-
D.
NFCChampionQuarterback
Indicates that the subject is a quarterback who has won the NFC Championship (i.e., led a team to an NFC Championship title).
-
E.
EaglesQuarterback
Indicates that the subject is a quarterback who plays for the Philadelphia Eagles football team.
- F. None of above. chosen
Provenance (4 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8a7f35481909f35feb94ef10e80 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf0e6e88190973694abe2990973 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.