Triple
T12538355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fakenham Magna |
E299763
|
entity |
| Predicate | hasRuralSettlementPattern |
P85002
|
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: [Fakenham Magna, hasRuralSettlementPattern, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralSettlementPattern Context triple: [Fakenham Magna, hasRuralSettlementPattern, true]
-
A.
isRuralSettlement
Indicates that a settlement is located in a rural area, typically characterized by low population density and limited urban infrastructure.
-
B.
hasRuralLocality
Indicates that an entity possesses, includes, or is associated with a rural locality (such as a village, hamlet, or countryside settlement) within its scope or jurisdiction.
-
C.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
D.
hasRuralLandscapeType
chosen
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
-
E.
hadPrimarySettlementPattern
Indicates that an entity exhibited or was characterized by a particular dominant form or arrangement of human settlement.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.