Triple
T5996654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Oki |
E133486
|
entity |
| Predicate | afterLeavingEmployer |
P15987
|
FINISHED |
| Object | focused on philanthropy |
—
|
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: focused on philanthropy | Statement: [Scott Oki, afterLeavingEmployer, focused on philanthropy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: afterLeavingEmployer Context triple: [Scott Oki, afterLeavingEmployer, focused on philanthropy]
-
A.
hadOccupationStatusUntil
Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
-
B.
reasonForLeaving
chosen
Indicates the cause, motivation, or circumstance that led an entity to depart or discontinue an association, position, or place.
-
C.
resumedOccupation
Indicates that an entity has returned to and continued a previous occupation or role after a period of interruption or absence.
-
D.
retiredFrom
Indicates that an entity has permanently stopped working for or being active in a specified organization, role, or activity.
-
E.
employment
Indicates a relationship where one entity hires, contracts, or otherwise engages another to perform work or services, typically in exchange for compensation.
- 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_69c00870ddbc81909880fa3864f4f38d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04e963f3c819082dd755e328ab947 |
completed | March 22, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69c049e152e88190979ab80cb9b50321 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:05 p.m.