Triple
T14746991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SkyCoaster |
E346497
|
entity |
| Predicate | hasCommonLocation |
P75187
|
FINISHED |
| Object | amusement parks |
—
|
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: amusement parks | Statement: [SkyCoaster, hasCommonLocation, amusement parks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonLocation Context triple: [SkyCoaster, hasCommonLocation, amusement parks]
-
A.
hasNearbyCommon
Indicates that two entities share at least one common element, feature, or connection that is located within a specified nearby distance or vicinity.
-
B.
hasLocationComponent
Indicates that something includes, is associated with, or is composed of a specific location-related part or element.
-
C.
hasCommonSpace
chosen
Indicates that two or more entities share access to the same physical or virtual area intended for joint or overlapping use.
-
D.
hasLocationRole
Indicates that an entity holds or plays a specific role in relation to a particular location (e.g., origin, destination, storage site, or operational area).
-
E.
hasTownCommon
Indicates that a place possesses or includes a town common, i.e., a shared public open space traditionally used by the local community.
- 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.