Triple
T1740302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afromontane forests |
E38217
|
entity |
| Predicate | characteristicClimate |
P193
|
FINISHED |
| Object | cool |
—
|
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: cool | Statement: [Afromontane forests, characteristicClimate, cool]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characteristicClimate Context triple: [Afromontane forests, characteristicClimate, cool]
-
A.
hasClimate
chosen
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
B.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
C.
climatologicalType
Indicates the classification of a climate or weather pattern that characterizes a place, period, or condition.
-
D.
glaciationCharacteristic
Indicates that one entity is a characteristic, feature, or property associated with the process or effects of glaciation of another entity.
-
E.
climaticChallenge
Indicates a relationship where an entity faces, contributes to, or is affected by significant difficulties or stresses arising from climate or weather 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab3c2559ac8190905186406fcaccb9 |
completed | March 6, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69aa61c4023c819099cbe439aefda71f |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.