Triple
T34820716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alidoro |
E1003763
|
entity |
| Predicate | replacesFairyTaleFigure |
P98140
|
FINISHED |
| Object | fairy godmother |
—
|
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: fairy godmother | Statement: [Alidoro, replacesFairyTaleFigure, fairy godmother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replacesFairyTaleFigure Context triple: [Alidoro, replacesFairyTaleFigure, fairy godmother]
-
A.
replacesCharacterInRole
chosen
Indicates that one character takes over and performs the same role previously held by another character.
-
B.
actsInSteadOf
Indicates that one entity performs an action or fulfills a role as a substitute or proxy for another entity.
-
C.
fictionalStandInFor
Indicates that one entity serves as a fictional or symbolic substitute representing another real or implied entity.
-
D.
replacedByInFilmAdaptation
Indicates that in a film adaptation, one entity (such as a character, object, or element) is substituted or superseded by another entity fulfilling a similar role.
-
E.
folkloreCharacter
Indicates that one entity is a character originating from the traditional stories, myths, or legends associated with the other 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: May 3, 2026, 4 p.m.