Triple
T6665260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fonds-Verrettes |
E151583
|
entity |
| Predicate | disasterVulnerability |
P44599
|
FINISHED |
| Object | deforestation-related flooding |
—
|
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: deforestation-related flooding | Statement: [Fonds-Verrettes, disasterVulnerability, deforestation-related flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disasterVulnerability Context triple: [Fonds-Verrettes, disasterVulnerability, deforestation-related flooding]
-
A.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
-
B.
hasNaturalHazardRisk
chosen
Indicates that an entity is exposed or subject to potential damage or impact from one or more natural hazards (e.g., earthquakes, floods, storms).
-
C.
supportsDisasterType
Indicates that one entity is capable of handling, responding to, or being applicable to a specified type of disaster.
-
D.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:02 p.m.