Triple
T11192650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Sandy Desert |
E264838
|
entity |
| Predicate | hasAverageRainfall |
P472
|
FINISHED |
| Object | less than 250 millimetres per year |
—
|
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: less than 250 millimetres per year | Statement: [Great Sandy Desert, hasAverageRainfall, less than 250 millimetres per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAverageRainfall Context triple: [Great Sandy Desert, hasAverageRainfall, less than 250 millimetres per year]
-
A.
averageAnnualPrecipitation
chosen
Indicates the typical total amount of precipitation an entity receives over the course of a year, averaged across multiple years.
-
B.
rainfallLevel
Indicates the amount or intensity of rainfall occurring at a given place and time.
-
C.
hasAverageSpringTemperature
Indicates that an entity is associated with a specific average temperature value measured over the spring season.
-
D.
averageAnnualSunshineDays
Indicates the typical number of days per year that a location experiences sunshine, averaged over a specified period.
-
E.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8be025481909d311b587418dfb2 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf4461c8190af84060f7db83211 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.