Triple

T7060483
Position Surface form Disambiguated ID Type / Status
Subject Odense E164202 entity
Predicate hasCulturalAttraction P3114 FINISHED
Object Odense Zoo E179747 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: Odense Zoo | Statement: [Odense, hasCulturalAttraction, Odense Zoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odense Zoo
Context triple: [Odense, hasCulturalAttraction, Odense Zoo]
  • A. Odense Zoo chosen
    Odense Zoo is a popular Danish zoological garden in the city of Odense, known for its diverse animal collections and family-friendly exhibits.
  • B. Tallinn Zoo
    Tallinn Zoo is a major zoological park in Tallinn, Estonia, known for its diverse collection of animal species and active conservation and education programs.
  • C. Kristiansand Zoo and Amusement Park
    Kristiansand Zoo and Amusement Park is one of Norway’s largest and most popular family attractions, combining a diverse animal park with themed rides and entertainment areas.
  • D. Ostrava Zoo
    Ostrava Zoo is a zoological garden in Ostrava, Czech Republic, known for its extensive collection of animal species and large naturalistic enclosures.
  • E. 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.
  • 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_69c688796c148190adb2f1596f595f22 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e459de348190912cd5326fb8bee0 completed March 27, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c788af20cc819084542035410aafbd completed March 28, 2026, 7:52 a.m.
Created at: March 27, 2026, 2:38 p.m.