Triple
T5667894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Etajima Island |
E124900
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Kure |
E498542
|
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: Kure | Statement: [Etajima Island, hasNearbyCity, Kure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kure Context triple: [Etajima Island, hasNearbyCity, Kure]
-
A.
Kure
chosen
Kure is a Japanese port city in Hiroshima Prefecture known historically as a major naval base and shipbuilding center.
-
B.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
-
C.
Kure District
Kure District is a major regional command of the Japan Maritime Self-Defense Force responsible for naval operations and support in the western part of Japan.
-
D.
Yokosuka
Yokosuka is a coastal city in Kanagawa Prefecture, Japan, known for its major naval base and strategic location at the mouth of Tokyo Bay.
-
E.
Hanko
Hanko is a coastal town in southern Finland known for its beaches, maritime heritage, and status as the country’s southernmost city.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023471f688190acec330596238a50 |
completed | March 22, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097dbdbc081909dd228c61461c5c8 |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:43 p.m.