Triple

T20163501
Position Surface form Disambiguated ID Type / Status
Subject Silver Star E491772 entity
Predicate locatedIn P40 FINISHED
Object Europa-Park 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: Europa-Park | Statement: [Silver Star, locatedIn, Europa-Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Europa-Park
Context triple: [Silver Star, locatedIn, Europa-Park]
  • A. Europa-Park chosen
    Europa-Park is one of Europe’s largest and most popular theme parks, located in Rust, Germany and known for its numerous themed areas representing different European countries and its wide variety of rides and attractions.
  • B. Heide Park
    Heide Park is one of Germany’s largest theme parks, featuring numerous roller coasters and family attractions, and is a major leisure destination in Lower Saxony.
  • C. Gardaland
    Gardaland is a major Italian theme park and resort near Lake Garda, known for its roller coasters, family attractions, and themed entertainment.
  • D. Efteling
    Efteling is a major Dutch fantasy-themed amusement park and resort known for its fairy-tale attractions and immersive storytelling.
  • E. Mirabilandia
    Mirabilandia is a major Italian amusement park near Ravenna, known for its large roller coasters, themed areas, and water park on the Adriatic coast.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66841b7d88190af3606f762d87b24 completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.