Triple
T25096081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 熊本市 |
E628592
|
entity |
| Predicate | 有名な時代背景 |
P561
|
FINISHED |
| Object | 江戸時代の武家文化 |
—
|
LITERAL 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: 江戸時代の武家文化 | Statement: [熊本市, 有名な時代背景, 江戸時代の武家文化]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 有名な時代背景 Context triple: [熊本市, 有名な時代背景, 江戸時代の武家文化]
-
A.
associatedWithNotableEra
Indicates that something has a significant connection or relevance to a historically or culturally notable period of time.
-
B.
hasHistoricSignificanceFor
Indicates that something holds notable historical importance or relevance for a particular entity or group.
-
C.
historicalBackground
Indicates that one entity provides contextual historical information or circumstances that help explain the origin, development, or significance of another entity.
-
D.
notableEra
chosen
Indicates the historical period or era for which an entity is especially recognized or significant.
-
E.
historicalNotability
Indicates that an entity is recognized as having significant importance, influence, or prominence in history.
- F. None of above.
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_69e2ff2f58e881908340527bc5d34f07 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f464b9651481908d4d7584717f5c59 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:25 a.m.