Triple
T6189549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aubrey–Maturin series |
E138150
|
entity |
| Predicate | coProtagonistOccupation |
P21567
|
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: [Aubrey–Maturin series, coProtagonistOccupation, physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coProtagonistOccupation Context triple: [Aubrey–Maturin series, coProtagonistOccupation, physician]
-
A.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
B.
coProtagonist
Indicates that two or more entities share the primary leading role together in the same narrative work.
-
C.
protagonistSocialStatus
Indicates the social standing or class position held by the story’s main character in relation to others in their society.
-
D.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
E.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
- 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_69c008a8fd408190b7ec6e42934974a6 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062192c5481909eb41f8c5d1208a3 |
completed | March 22, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c055fa0a808190bda37832e3ac150c |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:19 p.m.