Triple
T27010944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ritacuba Blanco |
E680380
|
entity |
| Predicate | hasVegetationBeltBelow |
P165875
|
FINISHED |
| Object | páramo |
—
|
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: páramo | Statement: [Ritacuba Blanco, hasVegetationBeltBelow, páramo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVegetationBeltBelow Context triple: [Ritacuba Blanco, hasVegetationBeltBelow, páramo]
-
A.
hasVegetationLayer
Indicates that an entity possesses a distinct layer or cover of vegetation as part of its structure or surface.
-
B.
hasVegetationRole
Indicates that an entity participates in or is assigned a specific functional role related to vegetation (such as growth, maintenance, or impact on plant life).
-
C.
hasRoadsideShelterbelts
Indicates that there are shelterbelt plantings or protective vegetation strips located along the roadside associated with the subject.
-
D.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
E.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
- F. None of above. chosen
Provenance (4 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65a9cb0bc8190bf8a9b319900bad5 |
completed | May 2, 2026, 8:12 p.m. |
Created at: April 27, 2026, 7:03 a.m.