Triple
T462383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limarí Valley |
E7366
|
entity |
| Predicate | dayNightTemperatureVariation |
P9975
|
FINISHED |
| Object | high diurnal range |
—
|
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: high diurnal range | Statement: [Limarí Valley, dayNightTemperatureVariation, high diurnal range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dayNightTemperatureVariation Context triple: [Limarí Valley, dayNightTemperatureVariation, high diurnal range]
-
A.
surfaceTemperatureRange
chosen
Indicates the range between the minimum and maximum surface temperatures observed or allowed for an entity.
-
B.
dayLengthCharacteristic
Indicates a relationship where an entity is characterized or defined by the length or duration of its day.
-
C.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
D.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
E.
environmentalCondition
Indicates the state or characteristics of the surrounding physical environment that affect or describe a situation, process, or entity.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efc09eac8190add4bb5823b53ba7 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede8eac081908dffade6a5e7950b |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.