Triple
T21699691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steinkjer municipality |
E535620
|
entity |
| Predicate | hasRuralFeature |
P85002
|
FINISHED |
| Object | agricultural areas |
—
|
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: agricultural areas | Statement: [Steinkjer municipality, hasRuralFeature, agricultural areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralFeature Context triple: [Steinkjer municipality, hasRuralFeature, agricultural areas]
-
A.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
B.
hasRuralLandscapeType
chosen
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
-
C.
hasRuralSection
Indicates that an entity includes, contains, or is associated with a portion or segment located in a rural area.
-
D.
hasRuralZoningCharacter
Indicates that a property or area possesses zoning attributes and regulations typical of rural land use.
-
E.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
- 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_69e0c46a6ee481908836e1420fb78c9b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef9b7de9888190bbca7717a32f9888 |
completed | April 27, 2026, 5:23 p.m. |
| PD | Predicate disambiguation | batch_69e6969113cc8190ab69855ef5667e4b |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:45 p.m.