Triple

T7320407
Position Surface form Disambiguated ID Type / Status
Subject Maastricht E168527 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Meerssen E691114 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: Meerssen | Statement: [Maastricht, hasNeighbouringMunicipality, Meerssen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meerssen
Context triple: [Maastricht, hasNeighbouringMunicipality, Meerssen]
  • A. Meerssen chosen
    Meerssen is a historic town and municipality in the Dutch province of Limburg, known for its medieval basilica and scenic location near Maastricht.
  • B. Maasbracht
    Maasbracht is a town in the Dutch province of Limburg, known as an inland port and industrial center along the River Meuse.
  • C. Wateringen
    Wateringen is a town in the western Netherlands that forms part of the municipality of Westland in the province of South Holland.
  • D. Zierikzee
    Zierikzee is a historic Dutch town on the island of Schouwen-Duiveland in Zeeland, known for its well-preserved medieval center and maritime heritage.
  • E. Sommelsdijk
    Sommelsdijk is a village in the Netherlands located on the island of Goeree-Overflakkee in the province of South Holland.
  • 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_69c68a5251508190ad68df4151cfeb04 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6ef1a7a3c81909504eb711056f302 completed March 27, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9abd319048190a24be5112c810489 completed March 29, 2026, 10:46 p.m.
Created at: March 27, 2026, 3:02 p.m.