Triple
T7335086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George FitzRoy, 1st Duke of Northumberland |
E169105
|
entity |
| Predicate | createdBaronOfPontefract |
P39376
|
FINISHED |
| Object | 1674 |
—
|
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: 1674 | Statement: [George FitzRoy, 1st Duke of Northumberland, createdBaronOfPontefract, 1674]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: createdBaronOfPontefract Context triple: [George FitzRoy, 1st Duke of Northumberland, createdBaronOfPontefract, 1674]
-
A.
createdBaronOrBaronessOf
chosen
Indicates that one entity granted or established the noble title of baron or baroness for another entity.
-
B.
createdBaronet
Indicates that one entity formally established or granted a baronetcy title to another entity.
-
C.
createdMarquess
Indicates that one entity formally established or granted the noble title of marquess to another entity.
-
D.
createdViscountIn
Indicates that an entity conferred or established the noble title of viscount in a particular place, context, or jurisdiction.
-
E.
createdDukeOfClarence
Indicates the relationship in which one entity formally granted or established the noble title "Duke of Clarence" for another entity.
- F. None of above.
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_69c68a568a6481908f11e20db7bc8446 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.