Triple

T4631920
Position Surface form Disambiguated ID Type / Status
Subject Mechelen E101436 entity
Predicate hasLandmark P105 FINISHED
Object Grote Markt E175340 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: Grote Markt | Statement: [Mechelen, hasLandmark, Grote Markt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grote Markt
Context triple: [Mechelen, hasLandmark, Grote Markt]
  • A. Grote Markt
    Grote Markt is the historic central market square of Haarlem in the Netherlands, known for its medieval architecture and prominent civic and religious buildings.
  • B. Grote Markt
    Grote Markt is the historic central market square of Gouda in the Netherlands, known for its traditional cheese market and surrounding medieval architecture.
  • C. Grote Markt chosen
    Grote Markt is the historic central square of Antwerp, Belgium, renowned for its ornate guildhalls, Brabo Fountain, and the Renaissance-style city hall.
  • D. Grand Place / Grote Markt
    Grand Place / Grote Markt is the ornate central square of Brussels, renowned for its opulent guildhalls, Town Hall, and status as a UNESCO World Heritage site.
  • E. Vredenburg square
    Vredenburg square is a central public square in the Dutch city of Utrecht, known as a major hub for shopping, events, and public transport.
  • 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_69bd43d2f1c081908cd4b7ec48ecc73d completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a342ffc8190a911d0598ed230bb completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfabeba3c8190b6515b99746f62a6 completed March 21, 2026, 1:56 a.m.
Created at: March 20, 2026, 1:13 p.m.