Triple
T2643752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairy Godmother |
E62936
|
entity |
| Predicate | franchiseRole |
P16873
|
FINISHED |
| Object | iconic magical helper in Disney canon |
—
|
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: iconic magical helper in Disney canon | Statement: [Fairy Godmother, franchiseRole, iconic magical helper in Disney canon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: franchiseRole Context triple: [Fairy Godmother, franchiseRole, iconic magical helper in Disney canon]
-
A.
franchiseOwner
Indicates that one entity holds the ownership and operating rights of a franchise granted by another entity.
-
B.
positionOnFranchise
chosen
Indicates the specific role, rank, or status an entity holds within a particular franchise or franchise-based organization.
-
C.
franchiseOf
Indicates that one entity operates as a franchise belonging to or licensed by another entity.
-
D.
roleInFranchiseHistory
Indicates the specific function, position, or contribution an entity has within the historical development or timeline of a franchise.
-
E.
typeOfFranchise
Indicates the specific category or kind of franchise that an entity belongs to within a broader franchising system.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd90046dc81908bab3440733f1e98 |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd814298c8190952f05aed43f6bb8 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.