Triple
T7971070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Individual Lightning Lane purchases |
E185322
|
entity |
| Predicate | queueEntranceName |
P80085
|
FINISHED |
| Object | Lightning Lane entrance |
—
|
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: Lightning Lane entrance | Statement: [Individual Lightning Lane purchases, queueEntranceName, Lightning Lane entrance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queueEntranceName Context triple: [Individual Lightning Lane purchases, queueEntranceName, Lightning Lane entrance]
-
A.
queueLocation
Indicates the place or position where an entity is arranged to wait in a queue or line.
-
B.
queueType
Indicates the classification or category of a queue that specifies how items in it are organized, prioritized, or processed.
-
C.
hasEntranceOn
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another entity.
-
D.
boarding
Indicates that one entity is getting onto or entering a vehicle, vessel, or similar conveyance associated with another entity.
-
E.
entersBy
Indicates that one entity moves into or gains access to another entity through a specified entrance, route, or means.
- 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_69ca8297699481909b75a405f01e03af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bd476108190988a75653a5c56d6 |
completed | March 31, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69cb047a8e4c81909b79e0f0bf56440c |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:13 p.m.