Triple
T34405948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vancouver Peninsula, Nunavut |
E883111
|
entity |
| Predicate | typicalPrecipitationLevel |
P103365
|
FINISHED |
| Object | low |
—
|
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: low | Statement: [Vancouver Peninsula, Nunavut, typicalPrecipitationLevel, low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPrecipitationLevel Context triple: [Vancouver Peninsula, Nunavut, typicalPrecipitationLevel, low]
-
A.
typicalPrecipitationPattern
chosen
Indicates the usual or characteristic pattern of precipitation associated with a place, time period, or climate condition.
-
B.
averageAnnualPrecipitation
Indicates the typical total amount of precipitation an entity receives over the course of a year, averaged across multiple years.
-
C.
hasHigherPrecipitationThan
Indicates that one location or time period experiences a greater amount of precipitation than another.
-
D.
hasHighPrecipitation
Indicates that a location or time period experiences a large amount of precipitation, such as rain or snow, relative to a defined standard or average.
-
E.
typicalWeatherFeature
Indicates a weather condition or pattern that commonly characterizes a place or time 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_69f349c1f2208190a09a489bb8b2719d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:59 a.m.