Triple
T21655330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beppu University |
E534448
|
entity |
| Predicate | locatedInAdministrativeTerritory |
P40
|
FINISHED |
| Object | Beppu |
E87326
|
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 | Statement: [Beppu University, locatedInAdministrativeTerritory, Beppu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beppu Context triple: [Beppu University, locatedInAdministrativeTerritory, Beppu]
-
A.
Beppu
chosen
Beppu is a famous Japanese city on the island of Kyushu renowned for its numerous hot springs and geothermal attractions.
-
B.
Beppu Jigoku
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.
-
C.
Shinshinotsu
Shinshinotsu is a small village in Hokkaido, Japan, known for its rural landscapes, hot springs, and agricultural character.
-
D.
Minamisaiwai
Minamisaiwai is a commercial and business district in Nishi Ward, Yokohama, known for its shopping facilities and proximity to Yokohama Station.
-
E.
Eboshidake
Eboshidake is a mountain in Japan, known as one of the peaks in the volcanic landscape of the Kirishima mountain range on Kyushu.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef59176b28819092384fc5f8968022 |
completed | April 27, 2026, 12:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a159843988190a16b4d26659e5403 |
completed | May 17, 2026, 7:23 p.m. |
Created at: April 16, 2026, 6:36 p.m.