Triple
T2293719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seto Inland Sea region |
E51562
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Kitakyushu |
E182027
|
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: Kitakyushu | Statement: [Seto Inland Sea region, majorCity, Kitakyushu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitakyushu Context triple: [Seto Inland Sea region, majorCity, Kitakyushu]
-
A.
Kitakyushu
chosen
Kitakyushu is a major industrial and port city located in Fukuoka Prefecture on Japan’s Kyushu island.
-
B.
Fukuoka
Fukuoka is a major Japanese city on the northern shore of Kyushu, known as an important economic, cultural, and transportation hub with a busy international port.
-
C.
Takamatsu
Takamatsu is a coastal city in Japan’s Kagawa Prefecture on the island of Shikoku, known as a regional transport hub and gateway to the Seto Inland Sea.
-
D.
Kurashiki
Kurashiki is a historic industrial and canal city in Okayama Prefecture, Japan, known for its well-preserved Edo-period merchant quarter and traditional warehouses.
-
E.
Yokkaichi
Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5d90d988190b3253b54e5bb5530 |
completed | March 7, 2026, 6:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf832772d08190842b1e1c1a87ea3a |
completed | March 22, 2026, 5:50 a.m. |
Created at: March 4, 2026, 7:48 p.m.