Triple
T13755360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narrator (Disney's "Cinderella") |
E330460
|
entity |
| Predicate | framingPhraseType |
P11925
|
FINISHED |
| Object | "once upon a time"-style introduction |
—
|
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: "once upon a time"-style introduction | Statement: [Narrator (Disney's "Cinderella"), framingPhraseType, "once upon a time"-style introduction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: framingPhraseType Context triple: [Narrator (Disney's "Cinderella"), framingPhraseType, "once upon a time"-style introduction]
-
A.
symbolicPhrase
Indicates a relationship where one entity is represented or expressed by a symbolic phrase associated with another entity.
-
B.
frameType
chosen
Indicates the specific structural or categorical kind of frame associated with an entity or relation.
-
C.
titlePhrase
Indicates that one entity is a phrase functioning as the title or name of another entity.
-
D.
mainPhrase
Indicates that the referenced phrase functions as the primary or central phrase within a larger linguistic or structural unit.
-
E.
framedBy
Indicates that one entity serves as a surrounding boundary or enclosing structure that visually or conceptually frames another entity.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02179c948190a652cc8c586e418f |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:09 p.m.