Triple
T12520570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jardí Botànic de Barcelona |
E299302
|
entity |
| Predicate | hasTypeOfClimateRepresented |
P193
|
FINISHED |
| Object | Mediterranean climate |
—
|
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: Mediterranean climate | Statement: [Jardí Botànic de Barcelona, hasTypeOfClimateRepresented, Mediterranean climate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfClimateRepresented Context triple: [Jardí Botànic de Barcelona, hasTypeOfClimateRepresented, Mediterranean climate]
-
A.
hasClimate
chosen
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
B.
hasClimateContext
Indicates that something is associated with, influenced by, or relevant to climate-related conditions, factors, or considerations.
-
C.
hasClimateSystem
Indicates that one entity possesses or is characterized by a particular climate system.
-
D.
climatologicalType
Indicates the classification of a climate or weather pattern that characterizes a place, period, or condition.
-
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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.