Triple
T21197388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Betsy (1965) |
E522360
|
entity |
| Predicate | windImpact |
P143522
|
FINISHED |
| Object | downed power lines across South Florida |
—
|
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: downed power lines across South Florida | Statement: [Hurricane Betsy (1965), windImpact, downed power lines across South Florida]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: windImpact Context triple: [Hurricane Betsy (1965), windImpact, downed power lines across South Florida]
-
A.
windSpeed
Indicates the measured or estimated rate at which wind is moving at a given location and time.
-
B.
terrainImpact
Indicates how the characteristics of the terrain influence or modify the outcome, behavior, or effectiveness of an action or interaction.
-
C.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
D.
windResistance
Indicates the degree to which an entity opposes or reduces the effect of wind acting upon it.
-
E.
impactOnField
Indicates the effect or influence that one entity, action, or development has on a particular field or domain.
- F. None of above. chosen
Provenance (4 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7333c9bac8190a203802a8b8e4143 |
completed | April 21, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5fa92a2448190896c022dd27511ad |
completed | April 20, 2026, 10:06 a.m. |
Created at: April 16, 2026, 3:11 p.m.