Triple
T8354642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 中部地方 |
E196653
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | 長野市 |
E78933
|
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: 長野市 | Statement: [中部地方, hasMajorCity, 長野市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 長野市 Context triple: [中部地方, hasMajorCity, 長野市]
-
A.
Nagano
chosen
Nagano is a city in central Japan best known internationally for hosting the 1998 Winter Olympic Games.
-
B.
Fuji City
Fuji City is an industrial city in Shizuoka Prefecture, Japan, known for its paper manufacturing industry and views of nearby Mount Fuji.
-
C.
Takayama
Takayama is a historic mountain city in Japan’s Gifu Prefecture, known for its well-preserved Edo-period streets, traditional wooden houses, and proximity to the Japanese Alps.
-
D.
Matsumoto
Matsumoto is a historic city in central Japan best known for its well-preserved Matsumoto Castle and as a gateway to the scenic Japanese Alps.
-
E.
Niigata
Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
- 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_69ca82f08b348190bfb7881944bbff6f |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8048edb88190a1980ad74818b898 |
completed | March 31, 2026, 8:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde7b2d00c8190b7df13a0853a6374 |
completed | April 2, 2026, 3:51 a.m. |
Created at: March 30, 2026, 5:59 p.m.