Triple
T23422582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. George, Utah |
E560700
|
entity |
| Predicate | averageLowTemperatureInJanuary |
P58439
|
FINISHED |
| Object | around freezing |
—
|
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: around freezing | Statement: [St. George, Utah, averageLowTemperatureInJanuary, around freezing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageLowTemperatureInJanuary Context triple: [St. George, Utah, averageLowTemperatureInJanuary, around freezing]
-
A.
averageJanuaryLowTemperature
chosen
Indicates the typical minimum daily temperature experienced in a location during the month of January.
-
B.
averageHighTemperatureInJanuary
Indicates the typical or mean value of the highest daily temperatures recorded during the month of January for a given location.
-
C.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
D.
averageJanuaryTemperatureRange
Indicates the range of typical average temperatures observed during the month of January for a given entity.
-
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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a54780d88190a7d5c1426b85b7fc |
completed | April 29, 2026, 6:29 a.m. |
| PD | Predicate disambiguation | batch_69f061f92da081908e7f1d0cd1e9b01c |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:46 p.m.