Triple
T14746964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SkyCoaster |
E346497
|
entity |
| Predicate | hasFirstInstallationYear |
P25196
|
FINISHED |
| Object | 1992 |
—
|
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: 1992 | Statement: [SkyCoaster, hasFirstInstallationYear, 1992]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstInstallationYear Context triple: [SkyCoaster, hasFirstInstallationYear, 1992]
-
A.
yearOfOriginalInstallation
chosen
Indicates the specific calendar year when something was first installed or put into initial operation.
-
B.
firstYearOfUse
Indicates the year in which something was first put into use or began being used.
-
C.
hasFirstProofYear
Indicates the year in which something was first proven or formally demonstrated to be true.
-
D.
yearOfUse
Indicates the specific year during which something was in use or actively utilized.
-
E.
firstInstalledInCity
Indicates that an entity was initially installed or put into operation in a particular city before any other location.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d116e88190828b163b18d80f68 |
completed | April 14, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.