Triple
T7520574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Misiones rainforest |
E177756
|
entity |
| Predicate | hasAverageTemperatureRange |
P4814
|
FINISHED |
| Object | warm year-round |
—
|
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: warm year-round | Statement: [Misiones rainforest, hasAverageTemperatureRange, warm year-round]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAverageTemperatureRange Context triple: [Misiones rainforest, hasAverageTemperatureRange, warm year-round]
-
A.
surfaceTemperatureRange
Indicates the range between the minimum and maximum surface temperatures observed or allowed for an entity.
-
B.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
C.
hasAverageSpringTemperature
Indicates that an entity is associated with a specific average temperature value measured over the spring season.
-
D.
growthTemperatureRange
Indicates the range of temperatures within which an organism or entity can grow or function effectively.
-
E.
averageTemperature
chosen
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
- 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_69c69f2891148190a484f3b8222c6f1b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c2ad6c8190b822c0a5b80e7829 |
completed | March 27, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d6bb808190bdd04499fd3bceb6 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:46 p.m.