Triple

T16065287
Position Surface form Disambiguated ID Type / Status
Subject Dutch Limburg E389715 entity
Predicate containsCity P294 FINISHED
Object Venlo 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: Venlo | Statement: [Dutch Limburg, containsCity, Venlo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Venlo
Context triple: [Dutch Limburg, containsCity, Venlo]
  • A. Venlo chosen
    Venlo is a historic city in the southeastern Netherlands, located near the German border on the river Meuse and known as a regional economic and logistics hub.
  • B. Roermond
    Roermond is a historic city in the southeastern Netherlands known for its medieval architecture, prominent churches, and large designer outlet shopping center.
  • C. Zwolle
    Zwolle is a historic Dutch city in the eastern Netherlands known for its medieval center, cultural heritage, and regional economic importance.
  • D. Culemborg
    Culemborg is a historic town in the Dutch province of Gelderland, known for its medieval center and role in the early Dutch colonial era.
  • E. Apeldoorn
    Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837bec688190a77ad347600b6bdc completed April 17, 2026, 12:49 a.m.
Created at: April 10, 2026, 4:57 a.m.