Triple
T2355274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kagoshima Prefecture |
E47538
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Kagoshima City |
E368366
|
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: Kagoshima City | Statement: [Kagoshima Prefecture, capital, Kagoshima City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kagoshima City Context triple: [Kagoshima Prefecture, capital, Kagoshima City]
-
A.
Kagoshima City
chosen
Kagoshima City is a major city in southern Japan’s Kyushu region, known for its active Sakurajima volcano, scenic bay setting, and role as a historic and industrial center.
-
B.
Kumamoto
Kumamoto is a major city on Japan’s Kyushu island, known for its historic Kumamoto Castle and role as the capital of Kumamoto Prefecture.
-
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.
Miyakojima City
Miyakojima City is a Japanese municipal city in Okinawa Prefecture known for governing the Miyako Islands, a subtropical island group famous for its beaches and coral reefs.
-
E.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc6fd4e488190b763a1c9b5d18f2c |
completed | March 7, 2026, 6:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfc4184b38819084c8c6d5c27d3906 |
completed | March 22, 2026, 10:27 a.m. |
Created at: March 4, 2026, 7:54 p.m.