Triple
T9473770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Fine |
E228458
|
entity |
| Predicate | narrativeRoleType |
P20934
|
FINISHED |
| Object | supporting character |
—
|
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: supporting character | Statement: [Dr. Fine, narrativeRoleType, supporting character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeRoleType Context triple: [Dr. Fine, narrativeRoleType, supporting character]
-
A.
narratorRole
Indicates that one entity serves as the narrator of another entity (such as a story, text, or media work), specifying the narrative role or function it performs.
-
B.
roleInStories
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
C.
narratorType
Indicates the narrative perspective or role from which a story or account is being told.
-
D.
narrativeRoleContext
Indicates the contextual narrative function or role an entity plays within a story or discourse (e.g., protagonist, antagonist, narrator) relative to other elements.
-
E.
hasNarrativeRole
chosen
Indicates that an entity participates in a narrative with a specific functional role (e.g., protagonist, antagonist, narrator) relative to the story.
- 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ff23aec8190b5341eb9bd816a43 |
completed | April 1, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69cca55f01b081908dc0f12eaa45f832 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:54 p.m.