Triple
T26715317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Pan films |
E673535
|
entity |
| Predicate | featuresMythicalBeing |
P83317
|
FINISHED |
| Object | fairy |
—
|
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 | Statement: [Peter Pan films, featuresMythicalBeing, fairy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresMythicalBeing Context triple: [Peter Pan films, featuresMythicalBeing, fairy]
-
A.
featuresMythicalObject
Indicates that something includes, presents, or prominently involves a mythical or legendary object.
-
B.
featuresCreatureOrLegend
chosen
Indicates that something includes, depicts, or prominently involves a particular creature or legendary being.
-
C.
hasMythologicalFeature
Indicates that an entity possesses a characteristic, attribute, or element derived from mythology or mythological beings.
-
D.
featuresMonster
Indicates that something includes or prominently presents a monster as part of its content or composition.
-
E.
hasMythologicalInhabitant
Indicates that a place or location is traditionally believed to be inhabited or occupied by a mythological being or creature.
- 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_69eecda3a22881908f3061c760b9d542 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: April 27, 2026, 3:37 a.m.