Triple
T19429763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köppen BSk |
E486079
|
entity |
| Predicate | hasSeasonalTemperatureRange |
P31603
|
FINISHED |
| Object | large temperature variations between seasons |
—
|
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: large temperature variations between seasons | Statement: [Köppen BSk, hasSeasonalTemperatureRange, large temperature variations between seasons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalTemperatureRange Context triple: [Köppen BSk, hasSeasonalTemperatureRange, large temperature variations between seasons]
-
A.
temperatureRangeVariant
Indicates a relationship where one temperature range is a variation or alternative form of another temperature range.
-
B.
humidityRange
Indicates the range of humidity values within which a condition, process, or entity is defined, operates, or remains valid.
-
C.
hasSeasonalNature
chosen
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
D.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
E.
hasTemperatureCategory
Indicates that an entity is associated with a specific qualitative temperature classification (e.g., hot, cold, warm).
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6321c774881908ba5bde20abd5adc |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.