Triple
T28951660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haunted Mansion (Magic Kingdom) |
E731030
|
entity |
| Predicate | hasInteractiveQueue |
P27769
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Haunted Mansion (Magic Kingdom), hasInteractiveQueue, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInteractiveQueue Context triple: [Haunted Mansion (Magic Kingdom), hasInteractiveQueue, Yes]
-
A.
hasQueue
Indicates that an entity maintains or is associated with a queue, typically representing an ordered list of items or tasks awaiting processing.
-
B.
hasInteractiveActivity
chosen
Indicates that an entity includes or is associated with an activity that requires active user participation or engagement.
-
C.
hasQueueAccessibility
Indicates that an entity provides accessible features or accommodations for people with disabilities in its queuing or waiting areas.
-
D.
hasInteractionMode
Indicates the way in which two entities engage or interact with each other, specifying the manner, channel, or pattern of their interaction.
-
E.
usesQueue
Indicates that one entity employs or relies on a queue mechanism to manage or process items, tasks, or messages.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fe59d11e9881909d2f33b7c717030e |
completed | May 8, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69fe394fdfbc8190a931926ae3635cbf |
completed | May 8, 2026, 7:28 p.m. |
Created at: April 28, 2026, 8:44 a.m.