Triple
T2909596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skylon Tower |
E63648
|
entity |
| Predicate | hasRevolvingRestaurantRotationPeriod |
P38870
|
FINISHED |
| Object | about 1 hour |
—
|
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: about 1 hour | Statement: [Skylon Tower, hasRevolvingRestaurantRotationPeriod, about 1 hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRevolvingRestaurantRotationPeriod Context triple: [Skylon Tower, hasRevolvingRestaurantRotationPeriod, about 1 hour]
-
A.
restaurantRotationPeriod
Indicates the length of time it takes for a restaurant’s offerings, such as menus or featured items, to complete one full cycle before repeating.
-
B.
hasSpinnerRide
Indicates that an entity offers, includes, or is associated with a spinner-style ride attraction.
-
C.
rotatesAmong
Indicates that an entity takes turns occupying or performing a role, position, or function in sequence with other entities.
-
D.
rotationPeriod_hours
chosen
Indicates the length of time, measured in hours, that an object takes to complete one full rotation on its axis.
-
E.
hasRotationPeriod
Indicates that one entity has a specified duration for completing a full rotation around its own axis.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0d329c88190b6fcaef0be1799eb |
completed | March 7, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69abdd1b77608190b20fc078fdb85e64 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:11 p.m.