Triple
T33009320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mashiki, Kumamoto Prefecture |
E844595
|
entity |
| Predicate | affectedAreaOf |
P1586
|
FINISHED |
| Object | Kumamoto earthquakes sequence of April 2016 |
—
|
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: Kumamoto earthquakes sequence of April 2016 | Statement: [Mashiki, Kumamoto Prefecture, affectedAreaOf, Kumamoto earthquakes sequence of April 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedAreaOf Context triple: [Mashiki, Kumamoto Prefecture, affectedAreaOf, Kumamoto earthquakes sequence of April 2016]
-
A.
affectedArea
chosen
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
B.
affectedLand
Indicates that a piece of land is impacted or influenced by a particular event, action, or condition.
-
C.
coveredArea
Indicates that one entity occupies or extends over a specific spatial region or surface area associated with another entity.
-
D.
areaOfSupport
Indicates the spatial region or domain within which an entity provides support, assistance, or backing to another.
-
E.
hasImpactArea
Indicates that an entity affects, influences, or has consequences within a specific area, domain, or scope.
- 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_69f3494e59f08190b9127c693e5c7e8f |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: May 1, 2026, 1:23 a.m.