Triple
T10570240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fukui Kenichi |
E249459
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fukui |
E1058689
|
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: Fukui | Statement: [Fukui Kenichi, familyName, Fukui]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fukui Context triple: [Fukui Kenichi, familyName, Fukui]
-
A.
Fukui
chosen
Fukui is a coastal city in central Japan known as the capital of Fukui Prefecture, with a strong industrial base and access to the Sea of Japan.
-
B.
Kaizuka
Kaizuka is a coastal city in Osaka Prefecture, Japan, known for its historical temples, traditional festivals, and proximity to Osaka Bay.
-
C.
Fujieda
Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
-
D.
Katsuragi-shi
Katsuragi-shi is a city located in Nara Prefecture in Japan, known for its historical sites and proximity to the Katsuragi mountain range.
-
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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52730fd4481908b3f4eb80ca209f2 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd27ee6ff881909fb0d1590580c4e8 |
completed | May 8, 2026, 12:01 a.m. |
Created at: April 6, 2026, 12:37 p.m.