Triple
T26977748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gran Rio |
E679504
|
entity |
| Predicate | populationDensityAlongBanks |
P171416
|
FINISHED |
| Object | low |
—
|
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: low | Statement: [Gran Rio, populationDensityAlongBanks, low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationDensityAlongBanks Context triple: [Gran Rio, populationDensityAlongBanks, low]
-
A.
populationDensity
Indicates the number of individuals or entities occupying a unit area within a given region.
-
B.
populationConcentration
Indicates the degree to which a population is densely gathered or distributed within a specific area or region.
-
C.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
-
D.
hasRiverBankSettlement
Indicates that a settlement is located on or directly adjacent to the bank of a river.
-
E.
hasPopulationConcentrationIn
Indicates that a population is densely or significantly clustered within a specified geographic 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_69eeeb507a7081909d516e1fa08b7d29 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 27, 2026, 6:43 a.m.