Triple
T17460529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naha City Hall |
E425138
|
entity |
| Predicate | hasOwner |
P347
|
FINISHED |
| Object | City of Naha |
—
|
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: City of Naha | Statement: [Naha City Hall, hasOwner, City of Naha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Naha Context triple: [Naha City Hall, hasOwner, City of Naha]
-
A.
City of Naha
chosen
The City of Naha is the capital and largest city of Okinawa Prefecture in Japan, known as a historic Ryukyuan cultural center and major regional port.
-
B.
City of Ginowan
The City of Ginowan is a municipality in central Okinawa, Japan, known for its coastal location, urban development, and proximity to U.S. military bases.
-
C.
Gotemba City
Gotemba City is a Japanese city in Shizuoka Prefecture near the southeastern base of Mount Fuji, known as a gateway for climbing and tourism around the mountain.
-
D.
Kamishihoro
Kamishihoro is a town in Hokkaido, Japan, known for its natural scenery, hot springs, and the historic Taushubetsu River Bridge within the Daisetsuzan mountain region.
-
E.
Nanyo City
Nanyo City is a municipality in northeastern Japan known for its hot springs, fruit production, and scenic rural landscapes.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451a3031c8190ab1dd0d41b002dd2 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.