Triple
T5952283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NL-DR |
E132427
|
entity |
| Predicate | codingSystemScope |
P43701
|
FINISHED |
| Object | first-level administrative subdivisions of the Netherlands |
—
|
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: first-level administrative subdivisions of the Netherlands | Statement: [NL-DR, codingSystemScope, first-level administrative subdivisions of the Netherlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codingSystemScope Context triple: [NL-DR, codingSystemScope, first-level administrative subdivisions of the Netherlands]
-
A.
codingSystemType
Indicates the classification or category of coding system used to encode or represent information in a given context.
-
B.
codingSystemContext
Indicates the coding system or classification framework within which a given code, identifier, or value is defined and interpreted.
-
C.
writingSystemScope
Indicates the range or extent of content, languages, or contexts to which a particular writing system applies or is used.
-
D.
encodingScope
chosen
Indicates the range or extent of content or information that is covered, represented, or captured by a particular encoding.
-
E.
standardizationScope
Indicates the extent or domain within which a standard or standardization effort is intended to apply or be enforced.
- 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:02 p.m.