Triple
T5944241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Desert |
E132239
|
entity |
| Predicate | typicalPrecipitation |
P472
|
FINISHED |
| Object | low annual precipitation |
—
|
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 annual precipitation | Statement: [High Desert, typicalPrecipitation, low annual precipitation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPrecipitation Context triple: [High Desert, typicalPrecipitation, low annual precipitation]
-
A.
averageAnnualPrecipitation
chosen
Indicates the typical total amount of precipitation an entity receives over the course of a year, averaged across multiple years.
-
B.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
C.
associatedWithPrecipitationType
Indicates that there is a relationship between an entity and a specific type or category of precipitation (such as rain, snow, or hail).
-
D.
typicalStormType
Indicates the kind of storm that is most commonly or characteristically associated with a given context or location.
-
E.
typicalWeatherNorthernHemisphere
Indicates the characteristic or commonly occurring weather conditions found in the Northern Hemisphere.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:01 p.m.