Triple
T6402114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest Florida |
E144086
|
entity |
| Predicate | hasWeatherRisk |
P14395
|
FINISHED |
| Object | hurricanes |
—
|
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: hurricanes | Statement: [Southwest Florida, hasWeatherRisk, hurricanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWeatherRisk Context triple: [Southwest Florida, hasWeatherRisk, hurricanes]
-
A.
hasSevereWeatherRisk
chosen
Indicates that an entity is exposed to or associated with a high likelihood of severe or hazardous weather conditions.
-
B.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
C.
weatherConsideration
Indicates that certain conditions, decisions, or actions take into account or are influenced by the current or expected weather.
-
D.
weatherCondition
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
E.
canProvideWeatherInformation
Indicates that an entity has the capability to supply or answer queries about weather-related data or conditions.
- 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_69c008dc56fc81908d43ffcc11d73bdd |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c068ade8c881908a0472f1de6b7c21 |
completed | March 22, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69c060f40ecc8190b1df17b96767675c |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:35 p.m.