Triple
T29570309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Apple Coaster |
E753284
|
entity |
| Predicate | windsAround |
P52689
|
FINISHED |
| Object | exterior of New York-New York Hotel and Casino |
—
|
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: exterior of New York-New York Hotel and Casino | Statement: [Big Apple Coaster, windsAround, exterior of New York-New York Hotel and Casino]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: windsAround Context triple: [Big Apple Coaster, windsAround, exterior of New York-New York Hotel and Casino]
-
A.
surrounds
Indicates that one entity is located all around another entity, enclosing or encircling it on multiple sides or completely.
-
B.
winding
Indicates that something follows a curving, twisting, or spiral path or shape rather than a straight one.
-
C.
around
Indicates that one entity is located or moves on all or most sides of another entity, encircling or surrounding it spatially.
-
D.
seDérouleAutourDe
Indicates that an event or process takes place around, centers on, or is organized about a particular entity or theme.
-
E.
runsAround
chosen
Indicates that one entity moves in a circular or surrounding path around another entity or area.
- 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_69f0ef7fcb4881908a933110adb9bda1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66d46180881908ff6b2ce3a27b9c0 |
completed | May 2, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 5:57 p.m.