Triple
T5624977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buin |
E147695
|
entity |
| Predicate | hasZoo |
P3480
|
FINISHED |
| Object | Buin Zoo |
E528342
|
NE 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: Buin Zoo | Statement: [Buin, hasZoo, Buin Zoo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buin Zoo Context triple: [Buin, hasZoo, Buin Zoo]
-
A.
Buin Zoo
chosen
Buin Zoo is a major zoological park in Buin, Chile, known for its diverse collection of animals and role as a popular family attraction and conservation site.
-
B.
Kankaria Zoo
Kankaria Zoo is a zoological park in Ahmedabad, India, known for its diverse collection of animals and its location beside the historic Kankaria Lake.
-
C.
Zona Zoo
Zona Zoo is the official student cheering section for University of Arizona athletics, known for its large, energetic presence at Wildcats sporting events.
-
D.
Beardsley Zoo
Beardsley Zoo is a historic zoological park in Bridgeport, Connecticut, known for its focus on North and South American species and conservation education.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c00906f2a88190a992c66b13d606d4 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02235b4e48190a529f70605bf47ca |
completed | March 22, 2026, 5:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a12b5bc8190a300a53a6423e81c |
completed | March 22, 2026, 9:07 p.m. |
Created at: March 22, 2026, 3:40 p.m.