Triple
T16428770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oniishibozu Jigoku |
E399014
|
entity |
| Predicate | hasNearbyAttraction |
P2064
|
FINISHED |
| Object | Kamado Jigoku |
E398395
|
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: Kamado Jigoku | Statement: [Oniishibozu Jigoku, hasNearbyAttraction, Kamado Jigoku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamado Jigoku Context triple: [Oniishibozu Jigoku, hasNearbyAttraction, Kamado Jigoku]
-
A.
Kamado Jigoku
chosen
Kamado Jigoku is one of Beppu’s famous “hell” hot spring attractions, known for its vividly colored boiling pools and dramatic geothermal scenery.
-
B.
Kaminaki
Kaminaki is a small traditional village located on the Lasithi Plateau in eastern Crete, Greece.
-
C.
Teppan Edo
Teppan Edo is a teppanyaki-style Japanese restaurant located in the Japan Pavilion at EPCOT in Walt Disney World Resort.
-
D.
Sekken
Sekken is an island in Møre og Romsdal county, Norway, situated in the Romsdalsfjord and known for its scenic landscapes and small rural community.
-
E.
Ranzan
Ranzan is a town in Saitama Prefecture, Japan, known for its scenic river valleys and rural landscapes northwest of Tokyo.
- 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_6a00458331748190a4bd1c5d2d466e6d |
completed | May 10, 2026, 8:44 a.m. |
Created at: April 10, 2026, 5:09 a.m.