Triple
T9386280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salome, Arizona |
E225912
|
entity |
| Predicate | averageLowTemperatureJanuary |
P58439
|
FINISHED |
| Object | around 40 °F |
—
|
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 40 °F | Statement: [Salome, Arizona, averageLowTemperatureJanuary, around 40 °F]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageLowTemperatureJanuary Context triple: [Salome, Arizona, averageLowTemperatureJanuary, around 40 °F]
-
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.
averageMinTemperatureColdestMonth
Indicates the lowest average minimum temperature recorded during the coldest month in a given location or period.
-
E.
averageColdestMonth
Indicates the month in which an entity experiences the lowest average temperature over a given period.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d3964c8190b0353f56df755db8 |
completed | April 1, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69cca53bd6ec81909bf403ce304e5c08 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:45 p.m.