Triple
T1074017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Indian Ocean Territory |
E23391
|
entity |
| Predicate | hasNoIndigenousPopulation |
P23975
|
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: [British Indian Ocean Territory, hasNoIndigenousPopulation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoIndigenousPopulation Context triple: [British Indian Ocean Territory, hasNoIndigenousPopulation, true]
-
A.
hasPermanentHumanPopulation
Indicates that an entity consistently hosts a stable, long-term community of human residents rather than only temporary or transient occupants.
-
B.
hasVerySmallResidentPopulation
Indicates that the subject location has a resident population that is extremely small in size.
-
C.
isLessPopulousThan
Indicates that one entity has a smaller population size than another entity.
-
D.
hasColonialHistoryWith
Indicates that one entity has a historical relationship of colonization or being colonized involving the other entity.
-
E.
hasLargestPopulationOn
Indicates that the subject entity has the greatest population among a specified set of entities within the context or scope defined by the object.
- 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92cbfd481909e2f928c1d06ebaa |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73844708190a16c9e9824ca2fb6 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8d5076481908640a0d873efdf14 |
completed | March 1, 2026, 10:08 p.m. |
Created at: March 1, 2026, 7:42 p.m.