Triple

T21369059
Position Surface form Disambiguated ID Type / Status
Subject Meerbeke E527002 entity
Predicate locatedIn P40 FINISHED
Object Ninove 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: Ninove | Statement: [Meerbeke, locatedIn, Ninove]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ninove
Context triple: [Meerbeke, locatedIn, Ninove]
  • A. Ninove chosen
    Ninove is a city in the Belgian province of East Flanders, known for its historical center and past role in major cycling events.
  • B. Neubauer
    Neubauer is a German surname borne by various notable individuals, including activists, politicians, and academics.
  • C. Napolitano
    Napolitano is an Italian surname commonly associated with individuals of Italian heritage, including notable figures in politics, academia, and organized crime history.
  • D. Merklín
    Merklín is a small municipality and village located in the Plzeň Region of the Czech Republic.
  • E. Sobotka
    Sobotka is a Czech surname most prominently associated with Bohuslav Sobotka, a former Prime Minister of the Czech Republic.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0ad04e081908ff02b2ee2bc7485 completed April 22, 2026, 11:27 a.m.
Created at: April 16, 2026, 5:09 p.m.