Triple
T14062172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinket Island |
E338371
|
entity |
| Predicate | naturalDisasterImpact |
P76614
|
FINISHED |
| Object | severe damage in 2004 tsunami |
—
|
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: severe damage in 2004 tsunami | Statement: [Trinket Island, naturalDisasterImpact, severe damage in 2004 tsunami]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalDisasterImpact Context triple: [Trinket Island, naturalDisasterImpact, severe damage in 2004 tsunami]
-
A.
causeOfDisaster
Indicates that the subject is responsible for bringing about or triggering the specified disaster.
-
B.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
-
C.
disasterLocation
chosen
Indicates the place where a disaster occurs or has its primary impact.
-
D.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
E.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568876308190840361dcaf10bd45 |
completed | April 14, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.