Triple

T7741551
Position Surface form Disambiguated ID Type / Status
Subject Silesian University of Technology E175521 entity
Predicate hasCampusIn P4623 FINISHED
Object Gliwice E333563 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: Gliwice | Statement: [Silesian University of Technology, hasCampusIn, Gliwice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gliwice
Context triple: [Silesian University of Technology, hasCampusIn, Gliwice]
  • A. Gliwice chosen
    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.
  • B. Chorzów
    Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
  • C. Katowice
    Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
  • D. Dąbrowa Górnicza
    Dąbrowa Górnicza is an industrial city in southern Poland’s Silesian Voivodeship, known for its heavy industry, mining heritage, and proximity to the unique Błędów Desert.
  • E. 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.
  • 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_69c6995f9c60819092e386192bd63c6f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7035df9348190ad3f3d845207bf4d completed March 27, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69e2d62cce008190ae269bbd289625a0 completed April 18, 2026, 12:54 a.m.
Created at: March 27, 2026, 4:07 p.m.