Triple

T6958704
Position Surface form Disambiguated ID Type / Status
Subject Maksimir Park E161312 entity
Predicate hasPart P35 FINISHED
Object Zagreb Zoo E160592 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: Zagreb Zoo | Statement: [Maksimir Park, hasPart, Zagreb Zoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zagreb Zoo
Context triple: [Maksimir Park, hasPart, Zagreb Zoo]
  • A. Zagreb Zoo chosen
    Zagreb Zoo is a zoological garden in Croatia’s capital city, known for its diverse collection of animal species and role in conservation and education.
  • B. Osijek Zoo and Aquarium
    Osijek Zoo and Aquarium is a zoological and aquatic park in Osijek, Croatia, featuring a variety of animal and fish species for conservation, education, and recreation.
  • C. Belgrade Zoo
    Belgrade Zoo is a zoological garden in central Belgrade, Serbia, known for its diverse animal collection and location within the historic Belgrade Fortress complex.
  • D. Plzeň Zoo
    Plzeň Zoo is a major zoological garden in the Czech city of Plzeň, known for its diverse animal collection and role in conservation and education.
  • E. Ostrava Zoo
    Ostrava Zoo is a zoological garden in Ostrava, Czech Republic, known for its extensive collection of animal species and large naturalistic enclosures.
  • 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dad240ac8190808014a5b4920b41 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75893a4808190b94a70d8823a01d3 completed March 28, 2026, 4:26 a.m.
Created at: March 27, 2026, 2:29 p.m.