Triple
T33291599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palais du Cinéma |
E852333
|
entity |
| Predicate | locatedInThemeParkArea |
P206410
|
FINISHED |
| Object | World Showcase |
E235330
|
NE 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: World Showcase | Statement: [Palais du Cinéma, locatedInThemeParkArea, World Showcase]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInThemeParkArea Context triple: [Palais du Cinéma, locatedInThemeParkArea, World Showcase]
-
A.
locatedInThemeParkType
Indicates that an entity is situated within or belongs to a specific type or category of theme park.
-
B.
locatedInAmusementPark
Indicates that one entity is situated within or is part of an amusement park.
-
C.
locatedInAttractionScene
Indicates that one entity is situated within or is part of the setting or scene of an attraction.
-
D.
hasThemeParkAreaType
Indicates that an entity is associated with a specific type or category of theme park area.
-
E.
locatedInParkVicinity
Indicates that an entity is situated in the area immediately surrounding or near a park.
- F. None of above. chosen
Provenance (5 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_69f349660ff48190a4568803d0b89941 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3543195134819085fc0badf52c3daa |
completed | June 19, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:32 a.m.