Triple
T16404882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beppu–Shimabara graben |
E398399
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Beppu City |
E1211727
|
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 City | Statement: [Beppu–Shimabara graben, near, Beppu City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beppu City Context triple: [Beppu–Shimabara graben, near, Beppu City]
-
A.
Beppu City
chosen
Beppu City is a famous hot spring resort city in Ōita Prefecture, Japan, renowned for its numerous onsen and unique geothermal attractions.
-
B.
Suwa City
Suwa City is a regional city in central Japan known for its scenic Lake Suwa, hot springs, precision manufacturing industry, and the historic Suwa Taisha shrine complex.
-
C.
Ibusuki
Ibusuki is a coastal city in Kagoshima Prefecture, Japan, best known for its natural hot springs and unique sand bath spas.
-
D.
Miyakonojō
Miyakonojō is a city in Miyazaki Prefecture on Japan’s Kyushu island, known for its agriculture and livestock production.
-
E.
Kagoshima City
Kagoshima City is a major city in southern Japan’s Kyushu region, known for its active Sakurajima volcano, scenic bay setting, and role as a historic and industrial center.
- 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_6a004f439d048190bf779cb263b7c7a7 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:09 a.m.