Triple

T17696660
Position Surface form Disambiguated ID Type / Status
Subject Arabella E441188 entity
Predicate mainCharacter P1183 FINISHED
Object Mandryka 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: Mandryka | Statement: [Arabella, mainCharacter, Mandryka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandryka
Context triple: [Arabella, mainCharacter, Mandryka]
  • A. Mandryka chosen
    Mandryka is a central male character in Richard Strauss’s opera "Arabella," portrayed as a wealthy landowner and the sincere, idealistic suitor of the heroine.
  • B. Morawa
    Morawa is a small rural town in Western Australia known for its grain farming, wildflower displays, and role as a service centre for the surrounding Mid West agricultural region.
  • C. Rakoń
    Rakoń is a mountain peak in the Western Tatras on the Polish-Slovak border, popular with hikers for its scenic ridge views.
  • D. Markusy
    Markusy is a village in northern Poland located in the Warmian-Masurian Voivodeship.
  • E. Jastarnia
    Jastarnia is a seaside resort town and fishing port on Poland’s Baltic coast, popular for its beaches and water sports.
  • 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e47156a8f8819080cc730f4e9bc6ad completed April 19, 2026, 6:08 a.m.
Created at: April 10, 2026, 10:04 a.m.