Triple
T17599700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skyline Rotorua |
E428660
|
entity |
| Predicate | lugeType |
P128177
|
FINISHED |
| Object | gravity-fuelled cart rides |
—
|
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: gravity-fuelled cart rides | Statement: [Skyline Rotorua, lugeType, gravity-fuelled cart rides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lugeType Context triple: [Skyline Rotorua, lugeType, gravity-fuelled cart rides]
-
A.
lugeVenue
Indicates that a location serves or is used as a venue for luge events or activities.
-
B.
skatingElementType
Indicates the specific type or category of a skating element performed or referenced in a skating activity or program.
-
C.
competitionLengthLugeWomen
Indicates the duration or length of a women's luge competition.
-
D.
typeOfSkiing
Indicates that one entity is a specific style, category, or kind of skiing in relation to another.
-
E.
typeOfSkier
Indicates the specific category or style of skier that an entity belongs to (e.g., beginner, expert, freestyle).
- F. None of above. chosen
Provenance (4 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46c4812d48190bf8e899fa8f7fbe4 |
completed | April 19, 2026, 5:46 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb50b448190a59dd4be33c76db7 |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:51 a.m.