Triple

T2018683
Position Surface form Disambiguated ID Type / Status
Subject Paleizenplein E44054 entity
Predicate faces P1699 FINISHED
Object Warandepark E224634 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: Warandepark | Statement: [Paleizenplein, faces, Warandepark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warandepark
Context triple: [Paleizenplein, faces, Warandepark]
  • A. Warandepark chosen
    Warandepark is a historic public park in central Brussels, Belgium, known for its formal layout, statues, and proximity to key government and royal buildings.
  • B. Sorghvliet park
    Sorghvliet park is a historic green park in The Hague, Netherlands, known for its landscaped grounds and proximity to important government residences.
  • C. Hanssenspark
    Hanssenspark is a public park in Vilvoorde, Belgium, known as one of the town’s main green recreational areas.
  • D. Kollen Park
    Kollen Park is a popular waterfront public park in Holland, Michigan, known for its scenic views of Lake Macatawa, walking paths, and community events.
  • E. Tivoli Park
    Tivoli Park is the largest and most famous public park in Ljubljana, Slovenia, known for its landscaped gardens, walking paths, and cultural venues.
  • 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_69a8891201bc8190aca837be6de41579 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb8cfa5c88190b55bce5db968665b completed March 7, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fe88e8881909f2e64ebe23b6d1f completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:38 p.m.