Triple

T20091270
Position Surface form Disambiguated ID Type / Status
Subject Zundert E496273 entity
Predicate hasVillage P4011 FINISHED
Object Wernhout 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: Wernhout | Statement: [Zundert, hasVillage, Wernhout]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wernhout
Context triple: [Zundert, hasVillage, Wernhout]
  • A. Wernhout chosen
    Wernhout is a village in the Dutch province of North Brabant, located within the municipality of Zundert near the Belgian border.
  • B. Wijster
    Wijster is a village in the Dutch province of Drenthe, known historically for its rural character and the nearby former waste disposal site that was the scene of a 1975 train hijacking.
  • C. Weerde
    Weerde is a village in the Flemish Brabant province of Belgium, known as a residential suburb within the municipality of Zemst.
  • D. Heurne
    Heurne is a small village in the municipality of Aalten in the Dutch province of Gelderland.
  • E. Wormhout
    Wormhout is a small commune in northern France, historically part of French Flanders and known for its rural character and World War II associations.
  • 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655edde08190a3f950e7f0c7cf9c completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 11:21 p.m.