Triple

T7670802
Position Surface form Disambiguated ID Type / Status
Subject Upper Silesian metropolitan area E173741 entity
Predicate hasMajorCity P316 FINISHED
Object Będzin E919940 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: Będzin | Statement: [Upper Silesian metropolitan area, hasMajorCity, Będzin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Będzin
Context triple: [Upper Silesian metropolitan area, hasMajorCity, Będzin]
  • A. Bielany
    Bielany is a northern district of Warsaw, Poland, known for its residential neighborhoods, green spaces, and connection to the city center via the Warsaw Metro.
  • B. Brzesko
    Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
  • C. Wojkowice chosen
    Wojkowice is a small town in southern Poland’s Silesian Voivodeship, situated in the industrial and urbanized Upper Silesian region.
  • D. Bolesławiec
    Bolesławiec is a historic town in southwestern Poland renowned for its traditional hand-decorated pottery.
  • E. Jaworzno
    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.
  • 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_69e6847ad9fc819085b0d6c886488c3b completed April 20, 2026, 7:54 p.m.
Created at: March 27, 2026, 4 p.m.