Triple

T20895976
Position Surface form Disambiguated ID Type / Status
Subject HSW E514535 entity
Predicate basedIn P40 FINISHED
Object Stalowa Wola, Poland 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: Stalowa Wola, Poland | Statement: [HSW, basedIn, Stalowa Wola, Poland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stalowa Wola, Poland
Context triple: [HSW, basedIn, Stalowa Wola, Poland]
  • A. Stalowa Wola chosen
    Stalowa Wola is an industrial city in southeastern Poland, historically known as a major center of heavy industry and steel production.
  • B. Tychy, Poland
    Tychy, Poland is an industrial city in the Silesian region known for its major automotive manufacturing plants and brewing industry.
  • C. Kunowice, Poland
    Kunowice, Poland is a village in western Poland near the German border, historically notable as the site of the 1759 Battle of Kunersdorf during the Seven Years' War.
  • D. Gorzów Wielkopolski, Poland
    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. Zabkowice Slaskie, Poland
    Ząbkowice Śląskie is a historic town in southwestern Poland’s Lower Silesia region, known for its medieval architecture and leaning tower.
  • 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_69e0b4f7ebe48190952a85547a0f31a1 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6d06233588190942493b709e30820 completed April 21, 2026, 1:18 a.m.
Created at: April 16, 2026, 12:47 p.m.