Triple
T16404583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umi Jigoku |
E398392
|
entity |
| Predicate | nameInJapanese |
P744
|
FINISHED |
| Object | 海地獄 |
E398392
|
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: 海地獄 | Statement: [Umi Jigoku, nameInJapanese, 海地獄]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 海地獄 Context triple: [Umi Jigoku, nameInJapanese, 海地獄]
-
A.
Yama Jigoku
Yama Jigoku is one of Beppu’s famous “hell” hot spring sites, known for its boiling, vividly colored pools and dramatic geothermal scenery.
-
B.
Naraka
Naraka is the concept of an underworld or hell in several Indian religions, where souls undergo punishment or purification after death.
-
C.
Valley of Hell
Valley of Hell is a dramatic geothermal area in Noboribetsu, Hokkaido, known for its steaming vents, sulfurous hot springs, and other volcanic activity that create an otherworldly landscape.
-
D.
Umi Jigoku
chosen
Umi Jigoku is one of Beppu’s famous “hell” hot springs in Japan, known for its striking cobalt-blue boiling water and scenic, geothermal landscape.
-
E.
Boca do Inferno
Boca do Inferno is a dramatic seaside cliff formation and blowhole on the Atlantic coast near Cascais, Portugal, known for its powerful waves and scenic views.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d1f16481909adb19dab86dcc72 |
completed | April 18, 2026, 6:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c6094e481909aa7402fd17fedae |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:09 a.m.