Triple
T29114689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calceolariaceae |
E737009
|
entity |
| Predicate | regionOfDiversity |
P12301
|
FINISHED |
| Object | Andes |
—
|
NE NERFINISHED |
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: Andes | Statement: [Calceolariaceae, regionOfDiversity, Andes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfDiversity Context triple: [Calceolariaceae, regionOfDiversity, Andes]
-
A.
notableDiversityRegion
Indicates that a region is recognized for having significant diversity, such as in its population, culture, or environment.
-
B.
centerOfDiversity
chosen
Indicates the location where a particular group, trait, or phenomenon exhibits its greatest variety or concentration of diversity.
-
C.
ethnicRegionOfFocus
Indicates that a particular ethnic group or ethnicity is the primary regional focus or subject of attention in a given context.
-
D.
hadPopulationDiversity
Indicates that an entity possessed a population characterized by a variety of distinct demographic or group attributes (such as ethnicity, culture, or other differentiating factors).
-
E.
diversity
Indicates the degree to which a set of entities differs along one or more dimensions such as type, attributes, or characteristics.
- 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_69f077ed54e08190bb02a744e8121a66 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
Created at: April 28, 2026, 11:21 a.m.