Triple
T16644255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakodate Bay |
E404423
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Mount Hakodate |
—
|
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: Mount Hakodate | Statement: [Hakodate Bay, hasViewOf, Mount Hakodate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Hakodate Context triple: [Hakodate Bay, hasViewOf, Mount Hakodate]
-
A.
Mount Hakodate
chosen
Mount Hakodate is a scenic mountain in Hakodate, Japan, famous for its panoramic night views over the city and harbor.
-
B.
Mount Rishiri
Mount Rishiri is a volcanic peak on Rishiri Island in Hokkaido, Japan, renowned for its conical shape, alpine flora, and scenic views over the Sea of Japan.
-
C.
Mount Akaishi
Mount Akaishi is one of Japan’s major high peaks, known for its rugged alpine terrain and scenic vistas within the country’s central mountain ranges.
-
D.
Mount Hakusan
Mount Hakusan is one of Japan’s “Three Holy Mountains,” a prominent volcanic peak revered in Shinto and Buddhist traditions for its spiritual significance and natural beauty.
-
E.
Mount Furutaka
Mount Furutaka is a mountain in Japan notable enough to have lent its name to the Imperial Japanese Navy cruiser Furutaka.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad3b12c8190a32e33d9ecff9dae |
completed | April 18, 2026, 12:36 p.m. |
Created at: April 10, 2026, 5:18 a.m.