Triple

T20671359
Position Surface form Disambiguated ID Type / Status
Subject Vive Kielce E508030 entity
Predicate homeVenueLocation P19090 FINISHED
Object Kielce, 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: Kielce, Poland | Statement: [Vive Kielce, homeVenueLocation, Kielce, Poland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kielce, Poland
Context triple: [Vive Kielce, homeVenueLocation, Kielce, Poland]
  • A. Kielce chosen
    Kielce is a city in south-central Poland known as an important regional center for industry, education, and culture.
  • B. Kozienice, Poland
    Kozienice is a historic town in east-central Poland known for its location along the Vistula River and proximity to the Kozienice Landscape Park.
  • C. Tychy, Poland
    Tychy, Poland is an industrial city in the Silesian region known for its major automotive manufacturing plants and brewing industry.
  • D. Mielec, Poland
    Mielec, Poland is an industrial city in southeastern Poland known for its aviation industry and aircraft manufacturing heritage.
  • E. Niepokalanów, Poland
    Niepokalanów, Poland is a Roman Catholic monastery complex founded by Saint Maximilian Kolbe that became one of the largest Franciscan religious communities and publishing centers in the world before World War II.
  • 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_69e0b4c1164881909a3bf1e3ddb2bc32 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b5c92aa8819096fbe0ca5101d01b completed April 20, 2026, 11:24 p.m.
Created at: April 16, 2026, 11:44 a.m.