Triple
T4862650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miller Outdoor Theatre |
E108696
|
entity |
| Predicate | hasLawnCapacity |
P22556
|
FINISHED |
| Object | several thousand additional spectators |
—
|
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: several thousand additional spectators | Statement: [Miller Outdoor Theatre, hasLawnCapacity, several thousand additional spectators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLawnCapacity Context triple: [Miller Outdoor Theatre, hasLawnCapacity, several thousand additional spectators]
-
A.
lawnCapacity
chosen
Indicates the maximum number of entities that can be accommodated or present on a given lawn at one time.
-
B.
hasLandscaping
Indicates that an entity possesses or is associated with designed outdoor grounds or landscape features.
-
C.
hasYard
Indicates that one entity possesses or includes a yard as part of its property or premises.
-
D.
hasNumberOfAcres
Indicates the specific quantity of land area, measured in acres, that is associated with an entity.
-
E.
hasStandingArea
Indicates that an entity includes or provides a designated area where people can stand.
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d60e47c819094b5fbe883db4c15 |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.