Triple
T22596874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fortune of War |
E574703
|
entity |
| Predicate | hasSecondaryProtagonistOccupation |
P148873
|
FINISHED |
| Object | physician |
—
|
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: physician | Statement: [The Fortune of War, hasSecondaryProtagonistOccupation, physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryProtagonistOccupation Context triple: [The Fortune of War, hasSecondaryProtagonistOccupation, physician]
-
A.
hasSecondaryProtagonist
Indicates that an entity (such as a work of fiction) features another character who serves as a secondary or supporting main protagonist alongside the primary one.
-
B.
hasCoProtagonistOccupation
Indicates that two or more co-protagonists share a specified occupation or professional role.
-
C.
secondaryProtagonistType
Indicates the role or category of a work’s secondary main character in relation to the primary protagonist.
-
D.
secondaryProtagonistCelebrated
Indicates that a secondary protagonist is being honored, praised, or widely recognized for their actions or role.
-
E.
coProtagonist
Indicates that two or more entities share the primary leading role together in the same narrative work.
- F. None of above. chosen
Provenance (4 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f16269a56881909bb5af0258150f93 |
completed | April 29, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 2:50 p.m.