Triple
T21009691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fukuoka-Kitakyushu metropolitan area |
E517511
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Miyawaka |
—
|
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: Miyawaka | Statement: [Fukuoka-Kitakyushu metropolitan area, hasMajorCity, Miyawaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miyawaka Context triple: [Fukuoka-Kitakyushu metropolitan area, hasMajorCity, Miyawaka]
-
A.
Miyawaka
chosen
Miyawaka is a city in Japan known for its location in northern Kyushu and its blend of industrial facilities and residential communities.
-
B.
Rankoshi
Rankoshi is a small town in Hokkaido, Japan, known for its rural landscapes and proximity to ski and hot spring resorts.
-
C.
Enyō
Enyō is a minor Greek goddess associated with war, destruction, and the bloody chaos of battle, often depicted as a companion of Ares.
-
D.
Teimei
Teimei is the posthumous name of the Japanese empress consort of Emperor Taishō, who served as Empress of Japan in the early 20th century.
-
E.
Miyaki
Miyaki is a town in Saga Prefecture, Japan, known for its cultural and municipal exchange partnerships with European communities such as Rheinbach in Germany.
- 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_69e0b50192308190a284fcc89dd23a49 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc3edc548190987a6c2c9936286a |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:53 p.m.