Triple

T6133624
Position Surface form Disambiguated ID Type / Status
Subject Leopoldstadt E136778 entity
Predicate hasPark P105 FINISHED
Object Prater park E56329 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: Prater park | Statement: [Leopoldstadt, hasPark, Prater park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prater park
Context triple: [Leopoldstadt, hasPark, Prater park]
  • A. Prater chosen
    Prater is a large public park and historic amusement area in Vienna, Austria, best known for its iconic Giant Ferris Wheel and extensive green spaces.
  • B. Prater Tower
    Prater Tower is a prominent amusement ride and observation tower located in Vienna’s historic Prater park.
  • C. Gellert Park
    Gellert Park is a public recreational park located in Daly City, California, offering open green spaces and community amenities for local residents.
  • D. Victoria Park
    Victoria Park is a public recreational park in Widnes, England, featuring green spaces, sports facilities, and community amenities.
  • E. Victoria Park
    Victoria Park is a residential and student-populated area in Manchester, England, known for its proximity to the city’s universities and diverse local communities.
  • 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_69c008a179388190a3b5a081bbf46d55 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05c7f34d081909e589b201b22be21 completed March 22, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1416e8fa8819092bf830cbaa56647 completed March 23, 2026, 1:34 p.m.
Created at: March 22, 2026, 4:15 p.m.