Triple
T14997091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun Messe Nichinan |
E373984
|
entity |
| Predicate | municipality |
P852
|
FINISHED |
| Object | Nichinan |
—
|
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: Nichinan | Statement: [Sun Messe Nichinan, municipality, Nichinan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nichinan Context triple: [Sun Messe Nichinan, municipality, Nichinan]
-
A.
Nichinan City
chosen
Nichinan City is a coastal municipality in southern Miyazaki Prefecture, Japan, known for its scenic Nichinan Coast, subtropical climate, and historic sites such as Obi Castle Town.
-
B.
Ōsaki
Ōsaki is a major commercial and business district in Tokyo known for its high-rise office complexes and convenient rail connections.
-
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.
Kurume
Kurume is a mid-sized city in southwestern Japan known for its traditional textile industry, ramen culture, and location along the Chikugo River in Fukuoka Prefecture.
-
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 (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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded718e4288190b5e144f82299a194 |
completed | April 15, 2026, 12:08 a.m. |
Created at: April 10, 2026, 2:54 a.m.