Triple

T12610763
Position Surface form Disambiguated ID Type / Status
Subject Bzura (Polish) E301113 entity
Predicate flowsNear P350 FINISHED
Object Zgierz 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: Zgierz | Statement: [Bzura (Polish), flowsNear, Zgierz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zgierz
Context triple: [Bzura (Polish), flowsNear, Zgierz]
  • A. Zgierz chosen
    Zgierz is a city in central Poland, historically part of the industrial Łódź region and notable for its textile industry and role in regional trade.
  • B. Zawiercie
    Zawiercie is a town in southern Poland’s Silesian Voivodeship, known historically as an industrial and railway hub near the Kraków-Częstochowa Upland.
  • C. Gorzów Wielkopolski
    Gorzów Wielkopolski is a city in western Poland, known as one of the two capitals of the Lubusz Voivodeship and an important regional industrial and cultural center.
  • D. Grudziądz
    Grudziądz is a historic city in northern Poland on the Vistula River, known for its medieval granaries and well-preserved Old Town.
  • E. Zabrze
    Zabrze is an industrial city in the Silesian region of southern Poland, historically known for coal mining and heavy industry.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954ea1d748190a848e8a7873e2ea5 completed April 10, 2026, 7:52 p.m.
Created at: April 9, 2026, 5:11 p.m.