Triple
T10942592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Pratt, 1st Earl Camden |
E258509
|
entity |
| Predicate | createdBaronInYear |
P39376
|
FINISHED |
| Object | 1765 |
—
|
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: 1765 | Statement: [Charles Pratt, 1st Earl Camden, createdBaronInYear, 1765]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: createdBaronInYear Context triple: [Charles Pratt, 1st Earl Camden, createdBaronInYear, 1765]
-
A.
createdBaronet
Indicates that one entity formally established or granted a baronetcy title to another entity.
-
B.
createdBaronOrBaronessOf
chosen
Indicates that one entity granted or established the noble title of baron or baroness for another entity.
-
C.
createdEarlBy
Indicates that an entity was granted or established as an earl by a specific creator or authority.
-
D.
createdViscountIn
Indicates that an entity conferred or established the noble title of viscount in a particular place, context, or jurisdiction.
-
E.
banYear
Indicates the year in which a ban was enacted or came into effect on the related entity or activity.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c33a7c8190b3347944f68ee431 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.