Triple
T10546771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akita Prefecture |
E248838
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Semboku |
E482317
|
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: Semboku | Statement: [Akita Prefecture, hasCity, Semboku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Semboku Context triple: [Akita Prefecture, hasCity, Semboku]
-
A.
Semboku
chosen
Semboku is a city in Akita Prefecture, Japan, known for its historic samurai district in Kakunodate and scenic Lake Tazawa.
-
B.
Shibukawa
Shibukawa is a city in Gunma Prefecture, Japan, known as a regional transport hub and gateway to nearby hot spring resorts such as Ikaho Onsen.
-
C.
Higashikawa
Higashikawa is a town in Hokkaido, Japan, known as a gateway to the Daisetsuzan mountain range and for its scenic natural landscapes.
-
D.
Noshiro
Noshiro is a coastal city in northern Japan known for its port on the Sea of Japan and its forestry and basketball traditions.
-
E.
Marugame
Marugame is a coastal city in Japan’s Kagawa Prefecture, known for Marugame Castle and its traditional uchiwa (paper fans) craftsmanship.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d526d20ef48190ab9f70d4ce5f2a11 |
completed | April 7, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7c93f048190a755addc0922064b |
completed | May 7, 2026, 8:36 p.m. |
Created at: April 6, 2026, 12:33 p.m.