Triple

T22071780
Position Surface form Disambiguated ID Type / Status
Subject De Munt E545424 entity
Predicate visibleFrom P1165 FINISHED
Object Muntplein 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: Muntplein | Statement: [De Munt, visibleFrom, Muntplein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muntplein
Context triple: [De Munt, visibleFrom, Muntplein]
  • A. Muntplein chosen
    Muntplein is a central square in Amsterdam, known as a busy traffic hub near the historic city center and the Munttoren (Mint Tower).
  • B. Troonplein
    Troonplein is a prominent square in Brussels, Belgium, located near key government buildings and the Royal Palace.
  • C. Kwaremontplein
    Kwaremontplein is a small square in the village of Kwaremont in East Flanders, Belgium, known for its location along the iconic Oude Kwaremont climb frequently featured in professional cycling races.
  • D. Ladeuzeplein
    Ladeuzeplein is a central and historic square in Leuven, Belgium, known as a prominent civic and cultural space surrounded by notable university buildings and public events.
  • E. Kennemerplein
    Kennemerplein is a public square in Haarlem, Netherlands, located directly in front of the city’s main railway station and serving as a key hub for local transit and pedestrian activity.
  • 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_69e11e344dfc81909b1d88a7221329c7 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12888dcc08190b18d3d44d09ab943 completed April 28, 2026, 9:37 p.m.
Created at: April 16, 2026, 8:28 p.m.