Triple
T26872964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justine Johnstone |
E676662
|
entity |
| Predicate | hasOccupationTransition |
P71077
|
FINISHED |
| Object | from entertainment to scientific research |
—
|
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: from entertainment to scientific research | Statement: [Justine Johnstone, hasOccupationTransition, from entertainment to scientific research]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOccupationTransition Context triple: [Justine Johnstone, hasOccupationTransition, from entertainment to scientific research]
-
A.
hasPastOccupation
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
B.
occupationalChange
chosen
Indicates a change in a person’s job, profession, or occupational status over time.
-
C.
hadOccupationStatusUntil
Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
-
D.
hasOccupationSequenceFrom
Indicates a relationship where one occupation or role follows another in a temporal sequence for the same entity.
-
E.
memberLaterOccupation
Indicates that an individual later held a particular occupation or position after an earlier point in time or role.
- 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_69eee9bb44988190b6e11652d028bc59 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f621cbc48881908d104c648c91c715 |
completed | May 2, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 5:33 a.m.