Triple
T22980694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Douglas – Van Johnson |
E571453
|
entity |
| Predicate | actorOccupation |
P146982
|
FINISHED |
| Object | film star |
—
|
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: film star | Statement: [Jeff Douglas – Van Johnson, actorOccupation, film star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: actorOccupation Context triple: [Jeff Douglas – Van Johnson, actorOccupation, film star]
-
A.
leadActorOccupation
Indicates that the occupation specified is the primary professional role of the lead actor in a given work or context.
-
B.
starOccupation
Indicates that an entity is the primary or featured performer in a particular occupation, role, or professional capacity.
-
C.
occupationInFilm
Indicates that an entity has a specific occupation or role within the context of a particular film.
-
D.
starredPerformerOccupation
chosen
Indicates the occupation or professional role of a performer who starred in a work or production.
-
E.
actorKnownFor
Indicates that an actor is widely recognized or notable for a particular work, role, or contribution.
- 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1829589548190863619aebcae026c |
completed | April 29, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:49 p.m.