Triple

T7503716
Position Surface form Disambiguated ID Type / Status
Subject Veghel E177331 entity
Predicate licensePlateRegion P76021 FINISHED
Object Netherlands E864 NE FINISHED

How this triple was built (3 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: Netherlands | Statement: [Veghel, licensePlateRegion, Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Netherlands
Context triple: [Veghel, licensePlateRegion, Netherlands]
  • A. Netherlands chosen
    The Netherlands is a Western European country known for its low-lying geography, extensive canal systems, and historically significant role in global trade and European politics.
  • B. Holland
    Holland is a historic coastal region in the western Netherlands that became the political and economic heartland of the emerging Dutch state.
  • C. Holland
    Holland is a regional less-than-truckload (LTL) freight carrier in the United States known for its operations in the Midwest and surrounding areas.
  • D. Holland
    Holland is a common English surname of Dutch origin, historically referring to people from the Holland region of the Netherlands.
  • E. Belgium and the Netherlands
    Belgium and the Netherlands are neighboring Western European countries known for their shared lowland geography, dense river networks, and closely intertwined cultural and economic ties.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: licensePlateRegion
Context triple: [Veghel, licensePlateRegion, Netherlands]
  • A. licensePlateOrigin chosen
    Indicates that a vehicle’s license plate was issued or originates from a particular jurisdiction or region.
  • B. labelRegion
    Indicates assigning a categorical or descriptive label to a specified region or area.
  • C. eligibleRegion
    Indicates the geographic area within which something (such as an offer, service, or rule) is valid, applicable, or permitted.
  • D. regionException
    Indicates an exception or exclusion to a rule, condition, or classification that applies specifically to a certain region or set of regions.
  • E. hasRegion
    Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
  • F. None of above.

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_69c69f2696688190915a8458f2398211 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f81b431481908214b69c6c8d83bc completed March 27, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c845e96a2c819099decde57a57bec3 completed March 28, 2026, 9:19 p.m.
PD Predicate disambiguation batch_69c6f4d266d88190982cf5d2ee2e9564 completed March 27, 2026, 9:21 p.m.
Created at: March 27, 2026, 3:44 p.m.