Triple
T18135283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Asama |
E434118
|
entity |
| Predicate | japaneseName |
P9882
|
FINISHED |
| Object | 浅間山 |
—
|
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: 浅間山 | Statement: [Mount Asama, japaneseName, 浅間山]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 浅間山 Context triple: [Mount Asama, japaneseName, 浅間山]
-
A.
Mount Asama
chosen
Mount Asama is an active and prominent volcano in central Honshu, Japan, known for its frequent eruptions and status as one of the country’s most closely monitored peaks.
-
B.
槍ヶ岳
槍ヶ岳 is a sharply pointed, spear-shaped peak in Japan’s Hida Mountains, renowned as one of the most iconic and challenging summits in the Northern Alps.
-
C.
Hakone volcano
Hakone volcano is an active complex volcano in Japan known for its caldera, hot springs, and role in the geologically dynamic region near Mount Fuji.
-
D.
Asama
Asama was a Japanese armored cruiser of the Imperial Japanese Navy that served prominently in the Russo-Japanese War.
-
E.
Asama
Asama is a high-speed Shinkansen train service in Japan that operates primarily on the Hokuriku Shinkansen line between Tokyo and Nagano.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de0677088190aaf584882b3d74a1 |
completed | April 19, 2026, 1:52 p.m. |
Created at: April 10, 2026, 10:29 a.m.