Triple

T7670797
Position Surface form Disambiguated ID Type / Status
Subject Upper Silesian metropolitan area E173741 entity
Predicate hasMajorCity P316 FINISHED
Object Jaworzno E251901 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: Jaworzno | Statement: [Upper Silesian metropolitan area, hasMajorCity, Jaworzno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jaworzno
Context triple: [Upper Silesian metropolitan area, hasMajorCity, Jaworzno]
  • A. Jaworzno chosen
    Jaworzno is a city in southern Poland, located in the Silesian Voivodeship and known for its industrial heritage and role in the Upper Silesian urban area.
  • B. Kociewie
    Kociewie is an ethnocultural region in northern Poland known for its distinct folk traditions, dialect, and rural landscapes.
  • C. Jedwabno
    Jedwabno is a small town in northern Poland located within the Warmian-Masurian Voivodeship, an area known for its lakes and forests.
  • D. Zduńska Wola
    Zduńska Wola is a town in central Poland known historically as a textile and industrial center.
  • E. Tczew
    Tczew is a historic town in northern Poland on the Vistula River, known for its important railway bridges and role as a regional transport hub.
  • 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_69e623a9711081908eac4238a717305c completed April 20, 2026, 1:01 p.m.
Created at: March 27, 2026, 4 p.m.