Triple

T21288884
Position Surface form Disambiguated ID Type / Status
Subject Michał Żebrowski E524734 entity
Predicate notableWork P4 FINISHED
Object Na dobre i na złe (TV series) 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: Na dobre i na złe (TV series) | Statement: [Michał Żebrowski, notableWork, Na dobre i na złe (TV series)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Na dobre i na złe (TV series)
Context triple: [Michał Żebrowski, notableWork, Na dobre i na złe (TV series)]
  • A. Na dobre i na złe chosen
    Na dobre i na złe is a long-running Polish medical drama television series centered on the professional and personal lives of doctors and staff at a fictional hospital.
  • B. Nałęczowianka
    Nałęczowianka is a popular Polish brand of bottled mineral water sourced from the spa town of Nałęczów.
  • C. Soleczniki
    Soleczniki is a town in southeastern Lithuania, known as the administrative center of the Šalčininkai District Municipality near the Polish border.
  • D. Dobra
    Dobra is a river in central Croatia known for flowing through Karlovac County and contributing to the region’s karst landscape and hydropower resources.
  • E. Dobrota
    Dobrota is a coastal town in Montenegro known for its historic stone houses and scenic waterfront along the Bay of Kotor.
  • 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d882408190a2300327cb73b7f6 completed April 21, 2026, 8:35 a.m.
Created at: April 16, 2026, 4:03 p.m.