Triple
T253360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isla Salas y Gómez |
E5384
|
entity |
| Predicate | hasPermanentHumanPopulation |
P8838
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Isla Salas y Gómez, hasPermanentHumanPopulation, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPermanentHumanPopulation Context triple: [Isla Salas y Gómez, hasPermanentHumanPopulation, false]
-
A.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
B.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
C.
historicallyInhabitedBy
Indicates that a place or region was inhabited by a particular group or population during some period in the past.
-
D.
hasPopulationType
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
-
E.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d5331b48190b3797fece8e60e20 |
completed | Feb. 28, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69a25b678d6c81909780e1995c1ca691 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c2ca46c81908c61696f31e59a98 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.