Triple
T24618567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Camp, California |
E609336
|
entity |
| Predicate | averageWinterClimate |
P156764
|
FINISHED |
| Object | cool, wet winters |
—
|
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: cool, wet winters | Statement: [French Camp, California, averageWinterClimate, cool, wet winters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageWinterClimate Context triple: [French Camp, California, averageWinterClimate, cool, wet winters]
-
A.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
B.
winterAverageTemperature
Indicates the typical or mean temperature recorded during the winter season for a given entity or location.
-
C.
averageWinterHighF
Indicates the typical or mean high temperature, measured in degrees Fahrenheit, during the winter season for the referenced entity.
-
D.
averageWinterHighTemperatureC
Indicates the typical maximum daily air temperature, measured in degrees Celsius, during the winter season for a given place or period.
-
E.
minimumWinterTemperature
Indicates the lowest temperature typically experienced during the winter season for the subject entity.
- F. None of above. chosen
Provenance (4 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_69e2c4d1140081909c58667bf68f80c3 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:32 a.m.