Triple

T3361525
Position Surface form Disambiguated ID Type / Status
Subject Southern Poland E70731 entity
Predicate hasMajorCity P316 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: [Southern Poland, hasMajorCity, Gliwice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gliwice
Context triple: [Southern Poland, hasMajorCity, 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. Wrocław
    Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
  • 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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb26906948190851a7b7d543a4d64 completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfa1b5c0e081909c9a923eef50018c completed March 22, 2026, 8 a.m.
Created at: March 8, 2026, 3:13 p.m.