Triple
T7422077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SEA LIFE Minnesota Aquarium |
E171272
|
entity |
| Predicate | hasApproximateExhibitCount |
P5288
|
FINISHED |
| Object | more than 30 exhibits |
—
|
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: more than 30 exhibits | Statement: [SEA LIFE Minnesota Aquarium, hasApproximateExhibitCount, more than 30 exhibits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateExhibitCount Context triple: [SEA LIFE Minnesota Aquarium, hasApproximateExhibitCount, more than 30 exhibits]
-
A.
numberOfExhibits
chosen
Indicates the total count of exhibits associated with a given entity or context.
-
B.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
-
C.
hasNearbyExhibits
Indicates that one entity has other exhibits located in close physical proximity to it.
-
D.
hasApproximateNumberOfMiniatures
Indicates that an entity is associated with an estimated or non-exact count of miniatures.
-
E.
hasExhibitionsAbout
Indicates that one entity organizes or presents exhibitions whose subject matter concerns another entity.
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ed29ec8190804564185fe20797 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.