Triple

T3898568
Position Surface form Disambiguated ID Type / Status
Subject Bielsko-Biała E90431 entity
Predicate formedFrom P402 FINISHED
Object Bielsko E90431 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: Bielsko | Statement: [Bielsko-Biała, formedFrom, Bielsko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bielsko
Context triple: [Bielsko-Biała, formedFrom, Bielsko]
  • A. Bielsko-Biała chosen
    Bielsko-Biała is a city in southern Poland at the foot of the Beskid Mountains, known as a regional industrial and cultural center formed from the historic towns of Bielsko and Biała.
  • B. Bolesławiec
    Bolesławiec is a historic town in southwestern Poland renowned for its traditional hand-decorated pottery.
  • 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. Hrubieszów
    Hrubieszów is a historic town in eastern Poland near the Ukrainian border, known for its multicultural heritage and location in the Lublin region.
  • E. Bielsk Podlaski
    Bielsk Podlaski is a historic town in northeastern Poland known for its multicultural heritage and location within the Podlasie region.
  • 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_69aed95d315881908cbf1bf4a7215fbf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecefa3608190a7a20ed6df6a64b2 completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0276db4e8819090ece339aba3a13b completed March 22, 2026, 5:31 p.m.
Created at: March 9, 2026, 3:21 p.m.