Triple
T25096121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 熊本市 |
E628592
|
entity |
| Predicate | 地震被害 |
P5296
|
FINISHED |
| Object | 2016年熊本地震で大きな被害を受けた |
—
|
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: 2016年熊本地震で大きな被害を受けた | Statement: [熊本市, 地震被害, 2016年熊本地震で大きな被害を受けた]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 地震被害 Context triple: [熊本市, 地震被害, 2016年熊本地震で大きな被害を受けた]
-
A.
facedMajorEarthquake
chosen
Indicates that an entity has experienced or been subjected to a significant or severe earthquake event.
-
B.
earthquakeCasualties
Indicates that an earthquake event resulted in a specified number or set of casualties (deaths and/or injuries).
-
C.
populationImpact2010Earthquake
Indicates the effect or consequences that the 2010 earthquake had on a population, such as changes in size, distribution, or demographic characteristics.
-
D.
impactOfDisasters
Indicates the effects or consequences that disasters have on entities, conditions, or outcomes.
-
E.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
- 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.