Triple
T20163447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raptor (Cedar Point) |
E491770
|
entity |
| Predicate | firstInPark |
P138898
|
FINISHED |
| Object | first inverted roller coaster at Cedar Point |
—
|
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: first inverted roller coaster at Cedar Point | Statement: [Raptor (Cedar Point), firstInPark, first inverted roller coaster at Cedar Point]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstInPark Context triple: [Raptor (Cedar Point), firstInPark, first inverted roller coaster at Cedar Point]
-
A.
startingPark
Indicates that an entity begins or initiates its activity, route, or presence from a specified park.
-
B.
positionInPark
Indicates that one entity occupies a specific location or spot within a park.
-
C.
openedInPark
Indicates that an entity was opened, inaugurated, or began operating within the boundaries of a park.
-
D.
inPark
Indicates that one entity is located within or inside the boundaries of a park.
-
E.
introducedInPark
Indicates that one entity caused two or more entities to meet or become acquainted with each other while they were in a park.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66841b7d88190af3606f762d87b24 |
completed | April 20, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:35 p.m.