Triple
T26657981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | camelback hills |
E666562
|
entity |
| Predicate | commonLocationOnCoaster |
P63190
|
FINISHED |
| Object | out-and-back layouts |
—
|
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: out-and-back layouts | Statement: [camelback hills, commonLocationOnCoaster, out-and-back layouts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonLocationOnCoaster Context triple: [camelback hills, commonLocationOnCoaster, out-and-back layouts]
-
A.
otherCarlsbadCoasterStation
Indicates that one entity is a different station associated with the Carlsbad Coaster than the primary or reference Carlsbad Coaster station.
-
B.
COASTERIs
Indicates that one entity is a coaster or functions in the role of a coaster in relation to another entity.
-
C.
sisterCoaster
Indicates that two roller coasters are related as “sister” rides, typically sharing a close design, theme, or manufacturer relationship.
-
D.
coasterType
chosen
Indicates the specific category or style of a coaster that characterizes its design or function.
-
E.
hasWaterCoaster
Indicates that an entity features or includes a water-based roller coaster attraction.
- 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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 27, 2026, 2:35 a.m.