Triple
T15753815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unalaska Airport |
E381914
|
entity |
| Predicate | hasChallengingWeather |
P17982
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Unalaska Airport, hasChallengingWeather, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChallengingWeather Context triple: [Unalaska Airport, hasChallengingWeather, yes]
-
A.
hasSevereWeatherRisk
Indicates that an entity is exposed to or associated with a high likelihood of severe or hazardous weather conditions.
-
B.
hasExtremeWeatherCharacteristic
chosen
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
C.
hasHighPrecipitation
Indicates that a location or time period experiences a large amount of precipitation, such as rain or snow, relative to a defined standard or average.
-
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.
hasMoreChallengingConditionsIn
Indicates that one situation, environment, or context involves stricter, harsher, or more demanding conditions than another within a specified domain.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.