Triple
T16428738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oniishibozu Jigoku |
E399014
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Beppu Jigoku |
E803210
|
NE FINISHED |
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: Beppu Jigoku | Statement: [Oniishibozu Jigoku, partOf, Beppu Jigoku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beppu Jigoku Context triple: [Oniishibozu Jigoku, partOf, Beppu Jigoku]
-
A.
Beppu Jigoku
chosen
Beppu Jigoku is a famous collection of vividly colored, steaming hot spring "hells" in Beppu, Japan, known for their dramatic geothermal landscapes and as a major sightseeing spot.
-
B.
Beppu
Beppu is a famous Japanese city on the island of Kyushu renowned for its numerous hot springs and geothermal attractions.
-
C.
Shiraike Jigoku
Shiraike Jigoku is a famous “white pond hell” hot spring in Beppu, Japan, known for its milky-white, geothermally heated waters and scenic garden setting.
-
D.
Minamisaiwai
Minamisaiwai is a commercial and business district in Nishi Ward, Yokohama, known for its shopping facilities and proximity to Yokohama Station.
-
E.
Shinshinotsu
Shinshinotsu is a small village in Hokkaido, Japan, known for its rural landscapes, hot springs, and agricultural character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328fd49708190abb5065fa430eff1 |
completed | April 18, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d447f5cc81908757869f2d1e94a1 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:09 a.m.