Triple
T15244313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norge 1:50 000 map series |
E364339
|
entity |
| Predicate | geographicCoverageType |
P117752
|
FINISHED |
| Object | continuous national coverage |
—
|
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: continuous national coverage | Statement: [Norge 1:50 000 map series, geographicCoverageType, continuous national coverage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicCoverageType Context triple: [Norge 1:50 000 map series, geographicCoverageType, continuous national coverage]
-
A.
hasGeographicType
Indicates that an entity is associated with or classified by a specific type or category of geographic feature or area.
-
B.
geographicAreaOfSupport
Indicates the geographic region or area within which support, assistance, or services are provided or applicable.
-
C.
regionCoverage
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
D.
geographicRangeType
Indicates the kind of geographic range or distribution pattern that characterizes where an entity occurs or is found.
-
E.
geographicReception
Indicates the geographic area or location where something (such as a work, message, or signal) is received, experienced, or has effect.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f306f08190be448b215d6c9b6c |
completed | April 15, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2ca6148190967c319728ec3661 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:13 a.m.