Triple
T33618469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isla Cabeza de Mechudo |
E861188
|
entity |
| Predicate | isSparselyInhabited |
P26438
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Isla Cabeza de Mechudo, isSparselyInhabited, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSparselyInhabited Context triple: [Isla Cabeza de Mechudo, isSparselyInhabited, true]
-
A.
hasLowPopulationDensity
chosen
Indicates that the number of individuals or entities per unit area in a given region is relatively small compared to typical or expected levels.
-
B.
isLessUrbanizedThan
Indicates that one place has a lower degree of urban development or urban characteristics compared to another place.
-
C.
isPredominantlyRural
Indicates that a place or region is characterized mainly by rural features, such as low population density and extensive non-urban land use.
-
D.
hasVerySmallResidentPopulation
Indicates that the subject location has a resident population that is extremely small in size.
-
E.
isLessPopulousThan
Indicates that one entity has a smaller population size than another entity.
- 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_69f34980fabc81909819228729a9ca84 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f819c400819080d17819b50f3aeb |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:41 a.m.