Triple
T2738264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greg Peters |
E60683
|
entity |
| Predicate | previousRoleAtNetflix |
P18982
|
FINISHED |
| Object | Chief Operating Officer |
—
|
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: Chief Operating Officer | Statement: [Greg Peters, previousRoleAtNetflix, Chief Operating Officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousRoleAtNetflix Context triple: [Greg Peters, previousRoleAtNetflix, Chief Operating Officer]
-
A.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
B.
followedByRoleInCareerOf
Indicates that one role or position directly succeeds another in the sequence of roles within a single entity’s career.
-
C.
hasProductionRole
Indicates that an entity holds a specific role or function in the production or creation process of another entity.
-
D.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
E.
officePreviouslyHeldBy
chosen
Indicates that a particular office or position was formerly occupied by a specified person or 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_69ab4b77febc819095603eb012cd141b |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb147a588190829b74fe05b3a114 |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd82859348190bce3be8f2e9d60ba |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.