Triple
T8354640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 中部地方 |
E196653
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | 静岡市 |
E185961
|
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: 静岡市 | Statement: [中部地方, hasMajorCity, 静岡市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 静岡市 Context triple: [中部地方, hasMajorCity, 静岡市]
-
A.
Shizuoka
chosen
Shizuoka is a coastal city in central Japan known for its views of Mount Fuji, green tea production, and role as the capital of Shizuoka Prefecture.
-
B.
Ōiso, Kanagawa
Ōiso, Kanagawa is a coastal town in Kanagawa Prefecture, Japan, known as a historic seaside resort and former retreat for prominent political figures such as Prime Minister Shigeru Yoshida.
-
C.
Fuji City
Fuji City is an industrial city in Shizuoka Prefecture, Japan, known for its paper manufacturing industry and views of nearby Mount Fuji.
-
D.
Yokkaichi
Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
-
E.
Shizuoka Prefecture
Shizuoka Prefecture is a coastal region in central Japan known for its views of Mount Fuji, tea production, and location along the Pacific coast between Tokyo and Nagoya.
- 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_69ce6ccf66d48190a457e0ea869b278e |
completed | April 2, 2026, 1:19 p.m. |
Created at: March 30, 2026, 5:59 p.m.