Triple
T25622398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNLV Special Events Center (during planning phase) |
E642334
|
entity |
| Predicate | hasPlannedSeatingType |
P167054
|
FINISHED |
| Object | indoor arena seating |
—
|
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: indoor arena seating | Statement: [UNLV Special Events Center (during planning phase), hasPlannedSeatingType, indoor arena seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedSeatingType Context triple: [UNLV Special Events Center (during planning phase), hasPlannedSeatingType, indoor arena seating]
-
A.
hasSeatingClassification
Indicates that an entity is assigned a specific type or category of seating arrangement or capacity.
-
B.
hadSeatType
Indicates that an entity was assigned or associated with a specific type or category of seat.
-
C.
hasPrioritySeating
Indicates that one entity provides or designates reserved or preferential seating for another entity.
-
D.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
E.
hasFlexibleSeating
Indicates that an entity provides seating arrangements that can be easily rearranged, adjusted, or reconfigured to suit different uses or preferences.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6653ccf648190b65fb1141928e47e |
completed | May 2, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f663ff176c8190aaadb475f75daee4 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 21, 2026, 5:05 p.m.