Triple
T21283510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keisei Ueno Station |
E524591
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Ueno Zoo |
—
|
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: Ueno Zoo | Statement: [Keisei Ueno Station, near, Ueno Zoo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ueno Zoo Context triple: [Keisei Ueno Station, near, Ueno Zoo]
-
A.
Ueno Zoo
chosen
Ueno Zoo is a historic and popular zoological garden in Tokyo, Japan, renowned for its diverse animal collection and giant pandas.
-
B.
Inokashira Park Zoo
Inokashira Park Zoo is a small, family-friendly zoo in Tokyo known for its collection of native Japanese animals, petting areas, and scenic setting within Inokashira Park.
-
C.
Maruyama Zoo
Maruyama Zoo is a popular zoological park in Sapporo, Japan, known for its diverse collection of animals and family-friendly exhibits set within the scenic Maruyama Park area.
-
D.
Nogeyama Zoo
Nogeyama Zoo is a free-admission municipal zoological park in Yokohama, Japan, known for its compact size and family-friendly animal exhibits.
-
E.
Kyoto Municipal Zoo
Kyoto Municipal Zoo is a historic public zoological park in Kyoto, Japan, known for its diverse animal exhibits and role in conservation and education.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d3dfbc819081bd876d95c7c480 |
completed | April 21, 2026, 8:35 a.m. |
Created at: April 16, 2026, 4:03 p.m.