Triple
T30854563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köppen Cfa |
E785883
|
entity |
| Predicate | hasMinimumColdestMonthTemperature |
P16762
|
FINISHED |
| Object | > 0 °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: > 0 °C | Statement: [Köppen Cfa, hasMinimumColdestMonthTemperature, > 0 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinimumColdestMonthTemperature Context triple: [Köppen Cfa, hasMinimumColdestMonthTemperature, > 0 °C]
-
A.
averageMinTemperatureColdestMonth
chosen
Indicates the lowest average minimum temperature recorded during the coldest month in a given location or period.
-
B.
averageColdestMonth
Indicates the month in which an entity experiences the lowest average temperature over a given period.
-
C.
minimumWinterTemperature
Indicates the lowest temperature typically experienced during the winter season for the subject entity.
-
D.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
E.
averageAnnualLowTemperature
Indicates the typical lowest temperature value recorded per year for a given place or period, averaged over multiple years.
- 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_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: April 29, 2026, 8:46 p.m.