Triple

T223195
Position Surface form Disambiguated ID Type / Status
Subject Red Light District (Amsterdam) E4260 entity
Predicate legalStatusOfProstitution P8349 FINISHED
Object legal and regulated 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: legal and regulated | Statement: [Red Light District (Amsterdam), legalStatusOfProstitution, legal and regulated]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalStatusOfProstitution
Context triple: [Red Light District (Amsterdam), legalStatusOfProstitution, legal and regulated]
  • A. legalStatusOfSlavery
    Indicates the legal condition or permissibility of slavery within a given jurisdiction, time, or context.
  • B. hasLegalStatus
    Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
  • C. criminalStatus
    Indicates the legal condition of an entity with respect to criminal law, such as whether they are accused, convicted, or cleared of a crime.
  • D. legalStatusOfReligion
    Indicates the formal legal standing, recognition, and regulatory conditions of a religion within a given jurisdiction or political entity.
  • E. deFactoStatus
    Indicates that one entity holds a role, position, or status in practice or by custom, even if it is not formally or legally recognized.
  • 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_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.
PDg Predicate description generation batch_69a25c2bda788190bcfc0bc94686f9e0 completed Feb. 28, 2026, 3:08 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.