Triple
T4534989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santo Antão |
E107385
|
entity |
| Predicate | hasMicroclimateArea |
P25732
|
FINISHED |
| Object | humid northern slopes |
—
|
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: humid northern slopes | Statement: [Santo Antão, hasMicroclimateArea, humid northern slopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMicroclimateArea Context triple: [Santo Antão, hasMicroclimateArea, humid northern slopes]
-
A.
hasClimateContext
Indicates that something is associated with, influenced by, or relevant to climate-related conditions, factors, or considerations.
-
B.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
C.
microhabitat
chosen
Indicates a specific, localized habitat or environmental niche within a larger habitat where an organism lives or an interaction occurs.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
hasMediterraneanClimate
Indicates that a place experiences a Mediterranean climate, typically characterized by mild, wet winters and hot, dry summers.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57a2301c8190aa59280a16750156 |
completed | March 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69bd521edd00819099dfccaa65dddd61 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:04 p.m.