Triple
T19825433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Haruna caldera |
E476310
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Shibukawa, Gunma |
—
|
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: Shibukawa, Gunma | Statement: [Mount Haruna caldera, near, Shibukawa, Gunma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shibukawa, Gunma Context triple: [Mount Haruna caldera, near, Shibukawa, Gunma]
-
A.
Numata, Gunma
Numata, Gunma is a city in Gunma Prefecture, Japan, known for its mountainous scenery, hot springs, and proximity to natural attractions such as lakes and ski areas.
-
B.
Moroyama, Saitama
Moroyama, Saitama is a town in Saitama Prefecture, Japan, known for its semi-rural character, residential communities, and proximity to the Tokyo metropolitan area.
-
C.
Shibukawa
chosen
Shibukawa is a city in Gunma Prefecture, Japan, known as a regional transport hub and gateway to nearby hot spring resorts such as Ikaho Onsen.
-
D.
Karuizawa, Nagano
Karuizawa, Nagano is a popular highland resort town in Japan known for its cool climate, scenic nature, and upscale shopping and leisure facilities.
-
E.
Hidaka, Saitama
Hidaka, Saitama is a city in Saitama Prefecture, Japan, known for its blend of suburban residential areas and natural surroundings, including parks and rivers.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656c9e7348190a569a40bd1fca6ba |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.