Triple
T6915881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deadhorse Airport |
E160049
|
entity |
| Predicate | hasWeatherConditions |
P2044
|
FINISHED |
| Object | arctic climate |
—
|
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: arctic climate | Statement: [Deadhorse Airport, hasWeatherConditions, arctic climate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWeatherConditions Context triple: [Deadhorse Airport, hasWeatherConditions, arctic climate]
-
A.
hasWeather
chosen
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
B.
weatherCondition
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
C.
canProvideWeatherInformation
Indicates that an entity has the capability to supply or answer queries about weather-related data or conditions.
-
D.
hasMinimumWeatherRequirements
Indicates that a subject is associated with the lowest acceptable set of weather conditions required for a particular activity, operation, or state to occur.
-
E.
weatherConsideration
Indicates that certain conditions, decisions, or actions take into account or are influenced by the current or expected weather.
- 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_69c6883ab1008190a07129ff06f625d9 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9dec058819094d1913a1e5218c0 |
completed | March 27, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:26 p.m.