Triple
T19525208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Łomża Governorate |
E488500
|
entity |
| Predicate | hadRuralPopulationMajority |
P47416
|
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: [Łomża Governorate, hadRuralPopulationMajority, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadRuralPopulationMajority Context triple: [Łomża Governorate, hadRuralPopulationMajority, true]
-
A.
isPredominantlyRural
chosen
Indicates that a place or region is characterized mainly by rural features, such as low population density and extensive non-urban land use.
-
B.
hasRuralAreaShare
Indicates the proportion of an entity’s total area or population that is classified as rural.
-
C.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
D.
hasLongRuralSectionsIn
Indicates that something (such as a route or infrastructure) contains extended stretches that pass through rural areas within a specified region or location.
-
E.
isLessUrbanizedThan
Indicates that one place has a lower degree of urban development or urban characteristics compared to another place.
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63639cfc08190894ac67f7d861a25 |
completed | April 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69e514c9c00481909b76bda67957e58b |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.