Triple
T23677388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hagerty Peterson & Company |
E584914
|
entity |
| Predicate | notableLeaderOccupation |
P47271
|
FINISHED |
| Object | businessman |
—
|
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: businessman | Statement: [Hagerty Peterson & Company, notableLeaderOccupation, businessman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLeaderOccupation Context triple: [Hagerty Peterson & Company, notableLeaderOccupation, businessman]
-
A.
notableHolderOccupation
chosen
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
-
B.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
C.
notableNamesakeOccupation
Indicates that an entity is named after a notable person whose occupation or professional role is specified by the related value.
-
D.
notableCharacterOccupation
Indicates that a notable character is associated with a specific occupation or professional role.
-
E.
notableLeaderAlias
Indicates that an alternative or commonly used name (alias) is associated with a notable leader.
- 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_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4f4d4388190a0e439f4df7a0f23 |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:51 p.m.