Triple
T21940747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natal, Rio Grande do Norte |
E541811
|
entity |
| Predicate | hasHighSunshine |
P2121
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Natal, Rio Grande do Norte, hasHighSunshine, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighSunshine Context triple: [Natal, Rio Grande do Norte, hasHighSunshine, true]
-
A.
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.
-
B.
hasMaximumSolarInsolation
chosen
Indicates that an entity receives the highest level of solar radiation or sunlight intensity compared to relevant alternatives or within a given context.
-
C.
sunshineHoursPerYear
Indicates the total number of hours in a year during which a location receives direct sunshine.
-
D.
hasHotSeason
Indicates that an entity experiences a distinct period of time characterized by hot or high-temperature weather conditions.
-
E.
hasMidnightSun
Indicates that a place experiences the natural phenomenon where the sun remains visible at local midnight for a continuous 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12420b1cc81909b375891aedc0979 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:55 p.m.