Triple
T390754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aquarium of the Bay |
E8873
|
entity |
| Predicate | numberOfAnimalsApprox |
P6210
|
FINISHED |
| Object | thousands of marine animals |
—
|
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: thousands of marine animals | Statement: [Aquarium of the Bay, numberOfAnimalsApprox, thousands of marine animals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAnimalsApprox Context triple: [Aquarium of the Bay, numberOfAnimalsApprox, thousands of marine animals]
-
A.
numberOfAnimals
chosen
Indicates the quantity of animals associated with a given entity or context.
-
B.
numberOfSpecies
Indicates the count of distinct species associated with a given entity or context.
-
C.
notableDomesticatedSpecies
Indicates that the subject is a species that is particularly well-known or significant as a domesticated animal.
-
D.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
-
E.
fauna
Indicates that an entity is an animal or part of the animal life associated with a particular place or context.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5d73e881909101308a583c8f13 |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96960608190bdd342da9c5ddb5e |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.