Triple

T7620456
Position Surface form Disambiguated ID Type / Status
Subject Berchem E172477 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Oud-Berchem E275226 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: Oud-Berchem | Statement: [Berchem, hasNeighbourhood, Oud-Berchem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oud-Berchem
Context triple: [Berchem, hasNeighbourhood, Oud-Berchem]
  • A. Diepenbeek
    Diepenbeek is a municipality in the Belgian province of Limburg, known for its blend of residential areas, industry, and the campus of Hasselt University.
  • B. Bellebeek
    Bellebeek is a small stream in Belgium that serves as a right-bank tributary of the River Dender.
  • C. Schaerbeek
    Schaerbeek is a multicultural municipality in the Brussels-Capital Region of Belgium, known for its Art Nouveau architecture and urban character.
  • D. Borgerhout chosen
    Borgerhout is a densely populated, multicultural district of the Belgian city of Antwerp, known for its vibrant street life and diverse communities.
  • E. Borsbeek
    Borsbeek is a small municipality in the Belgian province of Antwerp, known for its suburban character and proximity to the city of Antwerp.
  • 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_69c699506b308190826894dab1d9ea86 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa62870c8190b17f44eb7a3ff2ad completed March 27, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ca6d6a17b4819089eafc70ecc1f786 completed March 30, 2026, 12:32 p.m.
Created at: March 27, 2026, 3:55 p.m.