Triple

T12694658
Position Surface form Disambiguated ID Type / Status
Subject Creil E303298 entity
Predicate hasTwinTown P919 FINISHED
Object Chorzów E241511 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: Chorzów | Statement: [Creil, hasTwinTown, Chorzów]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chorzów
Context triple: [Creil, hasTwinTown, Chorzów]
  • A. Chorzów chosen
    Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
  • B. Gliwice
    Gliwice is a historic industrial and academic city in southern Poland’s Silesian region, known for its engineering university and the landmark Gliwice Radio Tower.
  • C. Stalowa Wola
    Stalowa Wola is an industrial city in southeastern Poland, historically known as a major center of heavy industry and steel production.
  • D. Wodzisław Śląski
    Wodzisław Śląski is a town in southern Poland known for its historic urban core and location in the industrial and mining region of Upper Silesia.
  • E. Sosnowiec
    Sosnowiec is an industrial city in southern Poland, located in the Silesian Voivodeship and known as part of the Upper Silesian metropolitan area.
  • 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_69d7bdef90d48190b46b88270e780946 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961ebd17081909f983567e4b36533 completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084a4c2cc81908c8acd3a1123208a completed May 10, 2026, 1:14 p.m.
Created at: April 9, 2026, 5:22 p.m.