Triple
T20076617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arctic (2018 film) |
E499882
|
entity |
| Predicate | leadActorCharacterOccupation |
P110410
|
FINISHED |
| Object | pilot |
—
|
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: pilot | Statement: [Arctic (2018 film), leadActorCharacterOccupation, pilot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorCharacterOccupation Context triple: [Arctic (2018 film), leadActorCharacterOccupation, pilot]
-
A.
leadActorOccupation
chosen
Indicates that the occupation specified is the primary professional role of the lead actor in a given work or context.
-
B.
leadActorRolePattern
Indicates a recurring or characteristic type of role that an actor typically plays as a leading performer in productions.
-
C.
followsCharacterOccupation
Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
-
D.
notableCharacterOccupation
Indicates that a notable character is associated with a specific occupation or professional role.
-
E.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643bcfd48190893abd3734f15cd3 |
completed | April 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:40 p.m.