Triple
T7155975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cranbrook, British Columbia, Canada |
E166811
|
entity |
| Predicate | hasWarmestMonth |
P47011
|
FINISHED |
| Object | July |
—
|
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: July | Statement: [Cranbrook, British Columbia, Canada, hasWarmestMonth, July]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWarmestMonth Context triple: [Cranbrook, British Columbia, Canada, hasWarmestMonth, July]
-
A.
averageWarmestMonth
chosen
Indicates the relationship between a place and the month in which its long-term average temperature is highest.
-
B.
averageMaxTemperatureWarmestMonth
Indicates the highest average temperature recorded in the warmest month of a given time period or location.
-
C.
wettestMonths
Indicates the months during which a location experiences the highest amount of precipitation compared to other months.
-
D.
averageColdestMonth
Indicates the month in which an entity experiences the lowest average temperature over a given period.
-
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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e80dafdc8190b24863b83f084d12 |
completed | March 27, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69c6e1caf4e48190b47bb398a3c1554d |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:47 p.m.