Triple
T16550531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capesterre-de-Marie-Galante |
E402058
|
entity |
| Predicate | seaLevelRiseRisk |
P64363
|
FINISHED |
| Object | coastal erosion and flooding risk |
—
|
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: coastal erosion and flooding risk | Statement: [Capesterre-de-Marie-Galante, seaLevelRiseRisk, coastal erosion and flooding risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seaLevelRiseRisk Context triple: [Capesterre-de-Marie-Galante, seaLevelRiseRisk, coastal erosion and flooding risk]
-
A.
hasRiskLevelComparedToNearbySea
Indicates the relative level of risk an entity has when compared to the nearby sea, such as in terms of exposure, danger, or vulnerability.
-
B.
hasCoastalRisk
chosen
Indicates that an entity is exposed to potential hazards or adverse impacts associated with coastal environments, such as flooding, erosion, or storm surge.
-
C.
seaLevelCharacteristic
Indicates a characteristic, property, or attribute specifically related to sea level.
-
D.
riskToEarth
Indicates that something poses a potential threat, danger, or harmful impact to Earth.
-
E.
hasTsunamiRisk
Indicates that the subject is exposed to or associated with a potential risk of tsunamis.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fc451dc8190b571d5010f4017f4 |
completed | April 18, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:15 a.m.