Triple
T6869055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soraku District |
E158490
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Seika |
E568908
|
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: Seika | Statement: [Soraku District, hasSettlement, Seika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seika Context triple: [Soraku District, hasSettlement, Seika]
-
A.
Seika
chosen
Seika is a town in Kyoto Prefecture, Japan, known for its residential communities and proximity to the Kansai Science City area.
-
B.
Jōkō
Jōkō is the Japanese honorific title traditionally given to a retired emperor who has abdicated the throne.
-
C.
Shōhō
Shōhō was a Japanese era name (nengō) of the early Edo period, used for a brief span in the mid-17th century.
-
D.
Shōhō
Shōhō was a Japanese light aircraft carrier of the Imperial Japanese Navy during World War II, notable for being the first Japanese carrier sunk in the war during the Battle of the Coral Sea.
-
E.
Nagako
Nagako, better known as Empress Kōjun, was the long-serving consort of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito of Japan.
- 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_69c68831e3648190a643c328122e4d43 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8a916a88190b81551731dff2898 |
completed | March 27, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748c0689081908d37d1530ed0f6a0 |
completed | March 28, 2026, 3:19 a.m. |
Created at: March 27, 2026, 2:22 p.m.