Triple
T21957429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nissaka-juku |
E542228
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kakegawa, Shizuoka |
—
|
NE NERFINISHED |
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: Kakegawa, Shizuoka | Statement: [Nissaka-juku, locatedIn, Kakegawa, Shizuoka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kakegawa, Shizuoka Context triple: [Nissaka-juku, locatedIn, Kakegawa, Shizuoka]
-
A.
Kakegawa City
chosen
Kakegawa City is a regional city in central Japan known for its historic Kakegawa Castle and high-quality green tea production.
-
B.
Oyama, Shizuoka
Oyama is a town in eastern Shizuoka Prefecture, Japan, known for its proximity to Mount Fuji and its scenic natural surroundings.
-
C.
Chigasaki
Chigasaki is a coastal city in Kanagawa Prefecture, Japan, known for its beaches, surfing culture, and relaxed Shōnan seaside atmosphere.
-
D.
Fujinomiya, Shizuoka Prefecture
Fujinomiya, Shizuoka Prefecture is a city at the southwestern base of Mount Fuji in Japan, known for its scenic views, shrines, and traditional cultural events.
-
E.
Susono, Shizuoka
Susono, Shizuoka is a city in eastern Shizuoka Prefecture, Japan, known for its proximity to Mount Fuji and its role as an industrial and residential hub in the region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1244108948190a08e6966e55c4acd |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:59 p.m.