Triple

T10100601
Position Surface form Disambiguated ID Type / Status
Subject Duchy of Teschen E216187 entity
Predicate hasMajorTown P316 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: [Duchy of Teschen, hasMajorTown, Bielsko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bielsko
Context triple: [Duchy of Teschen, hasMajorTown, 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. Brzesko
    Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
  • C. Bolesławiec
    Bolesławiec is a historic town in southwestern Poland renowned for its traditional hand-decorated pottery.
  • D. Zbrzyca
    Zbrzyca is a river in northern Poland that flows through the Pomeranian region before joining the Brda River.
  • E. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • 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_69ca83d039f08190b9d10363221c69fb completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cdd09878f88190bcfa2c81fb10e821 completed April 2, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69f63449892881909d361815cbfcdee5 completed May 2, 2026, 5:28 p.m.
Created at: March 30, 2026, 9:02 p.m.