Triple
T9082549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novy Urengoy |
E217668
|
entity |
| Predicate | hasExtremeWinterTemperatures |
P17982
|
FINISHED |
| Object | below −40 °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: below −40 °C | Statement: [Novy Urengoy, hasExtremeWinterTemperatures, below −40 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExtremeWinterTemperatures Context triple: [Novy Urengoy, hasExtremeWinterTemperatures, below −40 °C]
-
A.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
-
B.
hasExtremeWeatherCharacteristic
chosen
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
C.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
D.
winterTemperatureRange_C
Indicates the range of temperatures, in degrees Celsius, typically experienced during the winter season for the subject.
-
E.
winterAverageTemperature
Indicates the typical or mean temperature recorded during the winter season for a given entity or location.
- 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_69ca83d7a0388190ba1af89ed7ba36f9 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc960a2760819084aab611eb1c43a9 |
completed | April 1, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:13 p.m.