Triple
T33122622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ballroom 20 |
E847638
|
entity |
| Predicate | queuePattern |
P111408
|
FINISHED |
| Object | attendees often line up hours in advance |
—
|
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: attendees often line up hours in advance | Statement: [Ballroom 20, queuePattern, attendees often line up hours in advance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queuePattern Context triple: [Ballroom 20, queuePattern, attendees often line up hours in advance]
-
A.
queueType
Indicates the classification or category of a queue that specifies how items in it are organized, prioritized, or processed.
-
B.
queueStyle
Indicates the manner or configuration in which items or entities are ordered and processed within a queue.
-
C.
queueTypical
Indicates that an entity is in or follows a standard or commonly expected queueing order or behavior relative to others.
-
D.
queueBehavior
chosen
Indicates how an entity manages or responds to items or events in a queue, such as their order, timing, or handling strategy.
-
E.
queueElementType
Indicates the type or category of elements that are contained in or processed by a given queue.
- 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_69f349588f088190b7c9588860f72033 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d71a52288190bfdbb5c1913a7787 |
completed | May 3, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69f6d27224708190b31a541cebe0ff77 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:27 a.m.