Triple

T20188039
Position Surface form Disambiguated ID Type / Status
Subject Taron E492912 entity
Predicate locatedIn P40 FINISHED
Object Phantasialand 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: Phantasialand | Statement: [Taron, locatedIn, Phantasialand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phantasialand
Context triple: [Taron, locatedIn, Phantasialand]
  • A. Phantasialand chosen
    Phantasialand is a major German theme park known for its highly themed lands and innovative roller coasters and attractions.
  • B. King's Island
    King's Island is the historic core of Limerick city, Ireland, known for landmarks like King John’s Castle and its medieval streetscape.
  • C. Waldameer Park & Water World
    Waldameer Park & Water World is a historic family amusement and water park featuring roller coasters, water slides, and classic rides near the Lake Erie shoreline.
  • D. Kings Dominion
    Kings Dominion is a large amusement and theme park in Doswell, Virginia, known for its roller coasters and family attractions.
  • E. Wonderland Amusement Park
    Wonderland Amusement Park was a historic amusement park in Revere, Massachusetts, known for its early 20th-century rides, attractions, and seaside entertainment.
  • 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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66ad2c43c8190a2fc5ef2a0514e53 completed April 20, 2026, 6:05 p.m.
Created at: April 11, 2026, 11:37 p.m.