Triple
T17452457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Africarium |
E424946
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Africarium |
—
|
NE NERFINISHED |
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: Africarium | Statement: [Africarium, name, Africarium]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Africarium Context triple: [Africarium, name, Africarium]
-
A.
Africarium
chosen
Africarium is a unique oceanarium and exhibition complex in Wrocław, Poland, dedicated to showcasing the aquatic and coastal ecosystems of Africa.
-
B.
Artis Zoo
Artis Zoo is a historic zoological garden in Amsterdam known for its diverse animal collection, botanical gardens, and on-site aquarium and planetarium.
-
C.
Henry Vilas Zoo
Henry Vilas Zoo is a free, family-friendly zoological park in Madison, Wisconsin, known for its diverse animal exhibits and conservation and education programs.
-
D.
Hamura Zoo
Hamura Zoo is a small, family-friendly zoological park in Hamura, Tokyo, known for its approachable scale and educational animal exhibits.
-
E.
Amazona Zoo
Amazona Zoo is a family-friendly wildlife attraction in Cromer, England, featuring a variety of animals and conservation-focused exhibits.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4513faa0c8190961cf504c459bf34 |
completed | April 19, 2026, 3:51 a.m. |
Created at: April 10, 2026, 5:47 a.m.