Triple
T16022010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Tōya |
E388623
|
entity |
| Predicate | hasNearby |
P350
|
FINISHED |
| Object | Mount Usu |
—
|
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 Usu | Statement: [Lake Tōya, hasNearby, Mount Usu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Usu Context triple: [Lake Tōya, hasNearby, Mount Usu]
-
A.
Mount Usu
chosen
Mount Usu is an active stratovolcano in Hokkaido, Japan, known for its frequent eruptions and dramatic impact on the surrounding landscape.
-
B.
Mount Utsugi
Mount Utsugi is a prominent peak in Japan’s Kiso Mountains, known for its alpine scenery and popular hiking routes.
-
C.
Mount Tsurumi
Mount Tsurumi is a volcanic mountain in Ōita Prefecture, Japan, known for its panoramic views, seasonal foliage, and ropeway access from the hot spring resort city of Beppu.
-
D.
Mount Haruna
Mount Haruna is an active stratovolcano in Gunma Prefecture, Japan, known for its scenic caldera lake, hot springs, and popular hiking and sightseeing spots.
-
E.
Mount Maetokachi
Mount Maetokachi is a volcanic peak in Japan that forms part of the Tokachi Volcanic Group on the island of Hokkaido.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18323fc0881908bab7126d9ccf67d |
completed | April 17, 2026, 12:47 a.m. |
Created at: April 10, 2026, 4:55 a.m.