Triple
T5484214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central American dry forests |
E123538
|
entity |
| Predicate | climatePattern |
P193
|
FINISHED |
| Object | distinct wet and dry seasons |
—
|
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: distinct wet and dry seasons | Statement: [Central American dry forests, climatePattern, distinct wet and dry seasons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: climatePattern Context triple: [Central American dry forests, climatePattern, distinct wet and dry seasons]
-
A.
climatologicalType
Indicates the classification of a climate or weather pattern that characterizes a place, period, or condition.
-
B.
climateDriver
Indicates a factor or process that significantly influences or drives changes in climate conditions.
-
C.
shareClimateZones
Indicates that two entities are located in regions classified under the same climate zone or zones.
-
D.
hasClimate
chosen
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
E.
climatologicalSignificance
Indicates the degree to which something is important, influential, or relevant within the context of climate or long-term weather patterns.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd93e5d0f08190a6cc9fc408b7c5bb |
completed | March 20, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69bd91a73b148190a865243536a4fe76 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:10 p.m.