Triple
T1311363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanuatu |
E27996
|
entity |
| Predicate | climateVulnerability |
P14203
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Vanuatu, climateVulnerability, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: climateVulnerability Context triple: [Vanuatu, climateVulnerability, high]
-
A.
climateChangeEffect
Indicates how climate change influences or alters a particular entity, condition, or process.
-
B.
climateChangeIndicator
Indicates that the subject serves as a sign, measure, or signal of the presence, extent, or impact of climate change on the related object or context.
-
C.
climaticChallenge
chosen
Indicates a relationship where an entity faces, contributes to, or is affected by significant difficulties or stresses arising from climate or weather conditions.
-
D.
hasWaveClimate
Indicates a relationship where a location or coastal area is characterized by a particular pattern or regime of wave conditions (such as height, period, and direction).
-
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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c1560f888190bdd9107b08395e0b |
completed | March 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69a4bee9e4a88190b22ab2ee831a23c9 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.