Triple

T14225473
Position Surface form Disambiguated ID Type / Status
Subject Praga E352605 entity
Predicate contains P35 FINISHED
Object Warsaw Zoo E905831 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: Warsaw Zoo | Statement: [Praga, contains, Warsaw Zoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warsaw Zoo
Context triple: [Praga, contains, Warsaw Zoo]
  • A. Warsaw Zoo chosen
    Warsaw Zoo is a major zoological garden in Warsaw, Poland, known for its diverse animal collection and role in wildlife conservation and education.
  • B. Poznań Zoo
    Poznań Zoo is a major zoological garden in Poznań, Poland, known for its diverse collection of animal species and expansive natural enclosures.
  • C. Wrocław Zoo
    Wrocław Zoo is one of Poland’s oldest and largest zoological gardens, renowned for its extensive animal collection and the Africarium oceanarium complex.
  • D. Silesian Zoological Garden
    The Silesian Zoological Garden is a large zoo and recreational park in the Silesian region of Poland, known for its diverse animal collection and educational exhibits.
  • E. Prague Zoo
    Prague Zoo is a major zoological garden in Prague renowned for its extensive animal collections, conservation programs, and scenic location along the Vltava River.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6228e53c8190abbe4e2d88a7362a completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd281611b48190b787e38ba9c733a4 completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:06 a.m.