Triple
T29886863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | municipality of Jacobswoude |
E759034
|
entity |
| Predicate | hadAreaMeasurementSystem |
P1872
|
FINISHED |
| Object | metric system |
—
|
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: metric system | Statement: [municipality of Jacobswoude, hadAreaMeasurementSystem, metric system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadAreaMeasurementSystem Context triple: [municipality of Jacobswoude, hadAreaMeasurementSystem, metric system]
-
A.
usesMeasurementSystem
chosen
Indicates that one entity adopts or applies a particular system of measurement defined by another entity.
-
B.
meterSystem
Indicates that one entity uses, is measured in, or is associated with a particular system of meters or measurement units.
-
C.
hasInternationalSystem
Indicates that an entity is associated with, governed by, or operates under an internationally recognized system, framework, or standard.
-
D.
measuredAs
Indicates that one entity’s quantity, value, or property is expressed or recorded using another entity as its measurement or unit.
-
E.
hasMeasurement
Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
- 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_69f2245de2f48190a481404896b56254 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f676fdaee481908b38890b2e8aaf4b |
completed | May 2, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6 p.m.