Triple

T7670790
Position Surface form Disambiguated ID Type / Status
Subject Upper Silesian metropolitan area E173741 entity
Predicate hasMajorCity P316 FINISHED
Object Zabrze E526141 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: Zabrze | Statement: [Upper Silesian metropolitan area, hasMajorCity, Zabrze]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zabrze
Context triple: [Upper Silesian metropolitan area, hasMajorCity, Zabrze]
  • A. Zabrze chosen
    Zabrze is an industrial city in the Silesian region of southern Poland, historically known for coal mining and heavy industry.
  • B. Kluczbork
    Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
  • C. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • D. Zbrzyca
    Zbrzyca is a river in northern Poland that flows through the Pomeranian region before joining the Brda River.
  • E. Zawiercie
    Zawiercie is a town in southern Poland’s Silesian Voivodeship, known historically as an industrial and railway hub near the Kraków-Częstochowa Upland.
  • 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_69c699562484819086752091e3164a27 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701dd3c808190990e07ced94b3297 completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69e215ac56248190a75ad5ceb8152d5a completed April 17, 2026, 11:12 a.m.
Created at: March 27, 2026, 4 p.m.