Triple
T15967595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wet op de Raad van State |
E387234
|
entity |
| Predicate | heeftOnderwerp |
P56047
|
FINISHED |
| Object | hoogste bestuursrechter van Nederland |
—
|
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: hoogste bestuursrechter van Nederland | Statement: [Wet op de Raad van State, heeftOnderwerp, hoogste bestuursrechter van Nederland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heeftOnderwerp Context triple: [Wet op de Raad van State, heeftOnderwerp, hoogste bestuursrechter van Nederland]
-
A.
hasPrimarySubject
chosen
Indicates that an entity is the main or principal subject associated with another entity or resource.
-
B.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
C.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
D.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
E.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.