Triple
T223197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Light District (Amsterdam) |
E4260
|
entity |
| Predicate | regulationFocus |
P760
|
FINISHED |
| Object | public order |
—
|
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: public order | Statement: [Red Light District (Amsterdam), regulationFocus, public order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulationFocus Context triple: [Red Light District (Amsterdam), regulationFocus, public order]
-
A.
regulatoryDomain
Indicates that one entity defines or governs the rules, policies, or constraints under which another entity must operate.
-
B.
regulatesUse
Indicates that one entity controls, governs, or sets rules for how another entity may be used.
-
C.
primaryRegulator
Indicates that one entity serves as the main controlling or governing authority over another entity or process.
-
D.
relatedLegislation
Indicates that there exists a legislative document that is connected to, affects, or is otherwise relevant to the subject entity.
-
E.
governs
chosen
Indicates that one entity exercises authoritative control, direction, or rule over another entity or domain.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c7194fc8190a2d02d446ae3a75e |
completed | Feb. 28, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69a25b5617788190814358aee3f7ae37 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.