Triple

T22512208
Position Surface form Disambiguated ID Type / Status
Subject Silo District E556547 entity
Predicate near P350 FINISHED
Object De Waterkant NE NERFINISHED

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: De Waterkant | Statement: [Silo District, near, De Waterkant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: De Waterkant
Context triple: [Silo District, near, De Waterkant]
  • A. De Waterkant chosen
    De Waterkant is a trendy, historic neighborhood in Cape Town known for its cobbled streets, colorful cottages, and vibrant café and nightlife scene.
  • B. De Koperwiek
    De Koperwiek is a major shopping center in Capelle aan den IJssel, Netherlands, featuring a variety of retail stores, services, and dining options.
  • C. Gedempte Gracht
    Gedempte Gracht is a central shopping street in Zaandam, Netherlands, known for its variety of retail stores and pedestrian-friendly layout.
  • D. De Sluis
    De Sluis is a small settlement in the Dutch province of Zeeland, located within the municipality of Tholen.
  • E. De Waterstad
    De Waterstad is a residential neighborhood in the Dutch municipality of Hellevoetsluis, known for its waterside location and modern housing.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e555edc81909ca803587dafd747 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15d61a27881909faed490d2b65f39 completed April 29, 2026, 1:22 a.m.
Created at: April 16, 2026, 8:50 p.m.