Triple

T10686931
Position Surface form Disambiguated ID Type / Status
Subject Jaworzno E251901 entity
Predicate nearbyCity P350 FINISHED
Object Sosnowiec E426926 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: Sosnowiec | Statement: [Jaworzno, nearbyCity, Sosnowiec]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sosnowiec
Context triple: [Jaworzno, nearbyCity, Sosnowiec]
  • A. Sosnowiec chosen
    Sosnowiec is an industrial city in southern Poland, located in the Silesian Voivodeship and known as part of the Upper Silesian metropolitan area.
  • B. Skierniewice
    Skierniewice is a historic city in central Poland known for its horticultural research center and annual Skierniewice Fruit and Vegetable Festival.
  • C. Chorzów
    Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
  • D. Polkowice
    Polkowice is a town in southwestern Poland known for its copper mining industry and location within the Lower Silesian region.
  • E. Stalowa Wola
    Stalowa Wola is an industrial city in southeastern Poland, historically known as a major center of heavy industry and steel production.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd192220819088eff88148376266 completed April 9, 2026, 1:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd3cf630a8819094455fc45a815b83 completed May 8, 2026, 1:31 a.m.
Created at: April 8, 2026, 9:10 p.m.