Triple

T6613155
Position Surface form Disambiguated ID Type / Status
Subject Silesian Voivodeship E149284 entity
Predicate containsCity P294 FINISHED
Object Zawiercie E592792 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: Zawiercie | Statement: [Silesian Voivodeship, containsCity, Zawiercie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zawiercie
Context triple: [Silesian Voivodeship, containsCity, Zawiercie]
  • A. Zawiercie chosen
    Zawiercie is a town in southern Poland’s Silesian Voivodeship, known historically as an industrial and railway hub near the Kraków-Częstochowa Upland.
  • B. Zgierz
    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.
  • C. Zabrze
    Zabrze is an industrial city in the Silesian region of southern Poland, historically known for coal mining and heavy industry.
  • D. 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.
  • E. Wiszniewo
    Wiszniewo is a locality historically associated with the Second Polish Republic, known as an alternative name for the settlement of Wiszniew.
  • 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_69c687ebc680819094caf71faba2efe2 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af3890408190a0edf2f813b93196 completed March 27, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d316e50b548190b5f90a9753ad7cb0 completed April 6, 2026, 2:13 a.m.
Created at: March 27, 2026, 1:57 p.m.