Triple
T3067422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy Irvine as young Eric Lomax |
E62136
|
entity |
| Predicate | occupationOfCharacter |
P14167
|
FINISHED |
| Object | army 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: army officer | Statement: [Jeremy Irvine as young Eric Lomax, occupationOfCharacter, army officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationOfCharacter Context triple: [Jeremy Irvine as young Eric Lomax, occupationOfCharacter, army officer]
-
A.
followsCharacterOccupation
Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
-
B.
occupationOf
chosen
Indicates that one entity holds or performs the job, role, or profession associated with another entity.
-
C.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
D.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
E.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fea06881909e5251eea26599ac |
completed | March 8, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69ad9624b7a0819091d255614f5819ea |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.