Triple
T24122143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamamoto Town |
E597689
|
entity |
| Predicate | naturalDisasterType |
P64317
|
FINISHED |
| Object | earthquake |
—
|
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: earthquake | Statement: [Yamamoto Town, naturalDisasterType, earthquake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalDisasterType Context triple: [Yamamoto Town, naturalDisasterType, earthquake]
-
A.
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.
-
B.
disasterName
Indicates the specific name or title assigned to a particular disaster event.
-
C.
causeOfDisaster
Indicates that the subject is responsible for bringing about or triggering the specified disaster.
-
D.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
-
E.
climateEventType
Indicates the specific kind or category of a climate-related event associated with an entity or occurrence.
- 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_69e288c74200819098ab875b592cb39f |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dee47d5481909d61b8d948a24aa8 |
completed | April 29, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:05 p.m.