Triple
T7532862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujiyoshida |
E178069
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Oshino |
E378919
|
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: Oshino | Statement: [Fujiyoshida, borderedBy, Oshino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oshino Context triple: [Fujiyoshida, borderedBy, Oshino]
-
A.
Oshino
chosen
Oshino is a small village in Japan’s Yamanashi Prefecture, known for its traditional rural scenery and the crystal-clear spring ponds of Oshino Hakkai fed by Mount Fuji’s snowmelt.
-
B.
Ogawa
Ogawa is a town in Saitama Prefecture, Japan, known for its traditional Japanese paper (washi) production and its role as a local transport hub.
-
C.
Kamogawa
Kamogawa is a coastal city in Chiba Prefecture, Japan, known for its beaches, fishing industry, and the popular Kamogawa Sea World aquarium.
-
D.
Kamogawa
Kamogawa is a prominent river running through Kyoto, Japan, known for its scenic banks, cultural significance, and popular walking paths.
-
E.
Izumi
Izumi is a city located in Osaka Prefecture, Japan, known as a residential and commercial hub in the Kansai region.
- 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_69c69f2acdbc8190b5a8320168c1d0ba |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8493964819086aeddfa4872a70b |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7b042c8819098e345be61bbe943 |
completed | March 29, 2026, 6:33 a.m. |
Created at: March 27, 2026, 3:47 p.m.