Triple
T1512865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gulf of Bothnia |
E32052
|
entity |
| Predicate | typicalSurfaceTemperatureWinter |
P19296
|
FINISHED |
| Object | near 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: near 0 °C | Statement: [Gulf of Bothnia, typicalSurfaceTemperatureWinter, near 0 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSurfaceTemperatureWinter Context triple: [Gulf of Bothnia, typicalSurfaceTemperatureWinter, near 0 °C]
-
A.
typicalTemperature
chosen
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
B.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
C.
minSurfaceTemperature
Indicates the lowest temperature value observed or allowed on the surface of an object or environment.
-
D.
averageMinTemperatureColdestMonth
Indicates the lowest average minimum temperature recorded during the coldest month in a given location or period.
-
E.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
- 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9396e16408190b5e7b0ac43376d81 |
completed | March 5, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69a907aa67cc81909f00135365447399 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.