Triple
T30854565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köppen Cfa |
E785883
|
entity |
| Predicate | hasRequirementWarmestMonthTemperature |
P107019
|
FINISHED |
| Object | >= 22 °C |
—
|
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: >= 22 °C | Statement: [Köppen Cfa, hasRequirementWarmestMonthTemperature, >= 22 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRequirementWarmestMonthTemperature Context triple: [Köppen Cfa, hasRequirementWarmestMonthTemperature, >= 22 °C]
-
A.
hasMinTemperature
Indicates that something possesses or is associated with a specified minimum temperature value.
-
B.
hasTemperatureCriterion
chosen
Indicates that something is associated with a specific temperature-based condition or requirement that must be met.
-
C.
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.
-
D.
minimumWinterTemperature
Indicates the lowest temperature typically experienced during the winter season for the subject entity.
-
E.
hasAverageCoolTemperature
Indicates that something typically maintains or experiences a moderately low (cool) temperature over time.
- 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_69f224b91c14819084e764832fe67a57 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00b479c1588190af6e0698b7f8d7f7 |
completed | May 10, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_6a00b4158260819087d0cfad8b18cef4 |
completed | May 10, 2026, 4:36 p.m. |
Created at: April 29, 2026, 8:46 p.m.