Triple

T14782073
Position Surface form Disambiguated ID Type / Status
Subject Zawiercie County E347413 entity
Predicate hasCentralTown P1474 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: [Zawiercie County, hasCentralTown, Zawiercie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zawiercie
Context triple: [Zawiercie County, hasCentralTown, 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. Zwoleń
    Zwoleń is a historic town in east-central Poland known for its medieval origins and association with the Renaissance poet Jan Kochanowski.
  • D. Zawadzkie
    Zawadzkie is a small town in southwestern Poland known for its industrial heritage and location within the Opole region.
  • 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 (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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deca9de3f48190b7706925e2947cf5 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a4bb108e08190ac6036fc6259cd8b completed May 17, 2026, 11:13 p.m.
Created at: April 10, 2026, 1:31 a.m.