Triple
T9485551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Dream |
E228750
|
entity |
| Predicate | featuredAttractionType |
P8077
|
FINISHED |
| Object | audio-animatronic stage show |
—
|
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: audio-animatronic stage show | Statement: [Golden Dream, featuredAttractionType, audio-animatronic stage show]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredAttractionType Context triple: [Golden Dream, featuredAttractionType, audio-animatronic stage show]
-
A.
attractionType
chosen
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
-
B.
partOfAttractionType
Indicates that one attraction type is a component or subset of a broader, more general attraction type.
-
C.
hasAttractionType
Indicates that one entity is associated with a specific kind or category of attraction (e.g., tourist, cultural, natural).
-
D.
isMajorAttractionFor
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
-
E.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd804fb2b4819084c7f5a842dbe5a6 |
completed | April 1, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69cca561e6b0819090aa795f3c3a2083 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:55 p.m.