Triple
T20269977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiyero |
E499066
|
entity |
| Predicate | fateInMusical |
P139482
|
FINISHED |
| Object | transformed into the Scarecrow (implied) |
—
|
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: transformed into the Scarecrow (implied) | Statement: [Fiyero, fateInMusical, transformed into the Scarecrow (implied)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fateInMusical Context triple: [Fiyero, fateInMusical, transformed into the Scarecrow (implied)]
-
A.
fate
Indicates that an entity is destined or predetermined to experience a particular outcome or course of events beyond its control.
-
B.
fateInSequel
Indicates that the outcome or destiny of an entity is revealed or occurs in a subsequent work, installment, or sequel.
-
C.
fateInLegend
Indicates the ultimate outcome or destiny attributed to an entity within a particular legend or mythic narrative.
-
D.
fateInFilms
Indicates that the relationship concerns how fate or destiny is portrayed, referenced, or thematically expressed within films.
-
E.
fateInBooks
Indicates that a character’s destiny, outcome, or predetermined path is described or revealed within written works or books.
- F. None of above. chosen
Provenance (4 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e675dd7c58819095bbf4baeda04d6a |
completed | April 20, 2026, 6:52 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56702ad04819099c1c08f28d16809 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:42 p.m.