Triple

T2355187
Position Surface form Disambiguated ID Type / Status
Subject Amsterdam metropolitan area E47536 entity
Predicate hasPart P35 FINISHED
Object Velsen E83948 NE 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: Velsen | Statement: [Amsterdam metropolitan area, hasPart, Velsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Velsen
Context triple: [Amsterdam metropolitan area, hasPart, Velsen]
  • A. Velsen chosen
    Velsen is a municipality in the province of North Holland in the Netherlands, known for the port city of IJmuiden and its major steel industry.
  • B. Bloemendaal
    Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
  • C. Hulst
    Hulst is a historic fortified town and municipality in the Dutch province of Zeeland, near the border with Belgium.
  • D. Nuenen
    Nuenen is a village in the southern Netherlands, known for its association with both the painter Vincent van Gogh and computer scientist Edsger W. Dijkstra.
  • E. Vlaardingen
    Vlaardingen is a historic port city in the western Netherlands, situated along the Nieuwe Maas river and known for its former herring fishing industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a88a1b678c8190bce986922ba60ce0 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc6fd4e488190b763a1c9b5d18f2c completed March 7, 2026, 6:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69b48810202c8190a2a8d5ae849b6d9e completed March 13, 2026, 9:56 p.m.
Created at: March 4, 2026, 7:54 p.m.