Triple
T13542283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose’s Turn |
E323415
|
entity |
| Predicate | associatedWithCharacterArchetype |
P100869
|
FINISHED |
| Object | stage mother |
—
|
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: stage mother | Statement: [Rose’s Turn, associatedWithCharacterArchetype, stage mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCharacterArchetype Context triple: [Rose’s Turn, associatedWithCharacterArchetype, stage mother]
-
A.
usesCharacterArchetype
Indicates that one entity employs or incorporates the character archetype represented by another entity in its narrative or design.
-
B.
associatedWithCharacterRole
Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
-
C.
associatedWithCharacterGroup
Indicates that an entity has a connection or affiliation with a particular group of characters.
-
D.
hasArchetype
Indicates that one entity serves as the original model, pattern, or prototype upon which another entity is based or conceptually derived.
-
E.
associatedWithFilmCharacterType
chosen
Indicates that an entity has an association or connection with a particular type or category of film character.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafd8ba10819098faadcc6adf251e |
completed | April 12, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.