Triple
T28377259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomorrowland side of Disneyland Railroad route |
E718785
|
entity |
| Predicate | featuresShowScene |
P162840
|
FINISHED |
| Object | Primeval World Diorama |
—
|
NE NERFINISHED |
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: Primeval World Diorama | Statement: [Tomorrowland side of Disneyland Railroad route, featuresShowScene, Primeval World Diorama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresShowScene Context triple: [Tomorrowland side of Disneyland Railroad route, featuresShowScene, Primeval World Diorama]
-
A.
showsScene
chosen
Indicates that one entity (such as a media item or visual representation) depicts or presents a particular scene.
-
B.
featuresSceneFrom
Indicates that one entity (such as a work or media item) includes or presents a particular scene taken from another entity.
-
C.
sceneFeature
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
-
D.
featuresPreShow
Indicates that one entity includes or presents a pre-show segment or content associated with another entity.
-
E.
scenes
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fe766490c081908c49c8cc07d0ae9b |
completed | May 8, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69fe75bb5f4481908572a5ffcbdc5154 |
completed | May 8, 2026, 11:46 p.m. |
Created at: April 28, 2026, 1:03 a.m.