Triple
T6903460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SEA LIFE Busan Aquarium |
E159547
|
entity |
| Predicate | hasEducationalContentLevel |
P12602
|
FINISHED |
| Object | children |
—
|
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: children | Statement: [SEA LIFE Busan Aquarium, hasEducationalContentLevel, children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationalContentLevel Context triple: [SEA LIFE Busan Aquarium, hasEducationalContentLevel, children]
-
A.
hasEducationalAudience
chosen
Indicates that something is intended for or directed toward a specific educational audience or learner group.
-
B.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
C.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
D.
hasEducationalProfile
Indicates that an entity is associated with a specific educational profile, detailing its education-related characteristics, qualifications, or academic background.
-
E.
hasEducationalMaterial
Indicates that an entity provides, contains, or is associated with educational content or learning resources for 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_69c6883822e0819091e321526f20ae0a |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d988a5b48190a9238047e86f314c |
completed | March 27, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b7681481909ec50509b19fcf81 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:25 p.m.