Triple
T2636524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rancho Cucamonga, California |
E59758
|
entity |
| Predicate | averageWinterHighTemperature |
P32221
|
FINISHED |
| Object | around 60–70 °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 60–70 °F | Statement: [Rancho Cucamonga, California, averageWinterHighTemperature, around 60–70 °F]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageWinterHighTemperature Context triple: [Rancho Cucamonga, California, averageWinterHighTemperature, around 60–70 °F]
-
A.
averageWinterHighF
chosen
Indicates the typical or mean high temperature, measured in degrees Fahrenheit, during the winter season for the referenced entity.
-
B.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
C.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
D.
averageHighTemperatureInJanuary
Indicates the typical or mean value of the highest daily temperatures recorded during the month of January for a given location.
-
E.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8e1fffc81908e4921690098c8db |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.