Triple
T6397491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabrera |
E143975
|
entity |
| Predicate | humanSettlementLevel |
P70399
|
FINISHED |
| Object | minimal permanent population |
—
|
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: minimal permanent population | Statement: [Cabrera, humanSettlementLevel, minimal permanent population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: humanSettlementLevel Context triple: [Cabrera, humanSettlementLevel, minimal permanent population]
-
A.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
-
B.
urbanizationLevel
Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
-
C.
humanSettlementStatus
Indicates the classification of a place in terms of its status as a human settlement (e.g., whether and how it is recognized or designated as a populated place).
-
D.
cityLevel
Indicates the administrative or hierarchical rank of a city within a broader regional or national structure.
-
E.
populationConcentration
Indicates the degree to which a population is densely gathered or distributed within a specific area or region.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06896d180819091548a728e903184 |
completed | March 22, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69c060f25c088190b433f78553ff1d84 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623d23448190a75cf5d802fc0a02 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:35 p.m.