Triple
T9296322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Futaba, Fukushima Prefecture |
E223646
|
entity |
| Predicate | hasDisasterType |
P64317
|
FINISHED |
| Object | nuclear disaster impact zone |
—
|
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: nuclear disaster impact zone | Statement: [Futaba, Fukushima Prefecture, hasDisasterType, nuclear disaster impact zone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisasterType Context triple: [Futaba, Fukushima Prefecture, hasDisasterType, nuclear disaster impact zone]
-
A.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
B.
supportsDisasterType
Indicates that one entity is capable of handling, responding to, or being applicable to a specified type of disaster.
-
C.
notableDisasterType
chosen
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
D.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
-
E.
causeOfDisaster
Indicates that the subject is responsible for bringing about or triggering the specified disaster.
- 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_69ca8423edb08190bc0c91287a484768 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd089c9c588190967404c9eb938dfb |
completed | April 1, 2026, 11:59 a.m. |
| PD | Predicate disambiguation | batch_69cc7a5aeb748190afb89c6bbd2a6d6f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:36 p.m.