Triple

T12952500
Position Surface form Disambiguated ID Type / Status
Subject Cieszyn County E309925 entity
Predicate capital P234 FINISHED
Object Cieszyn NE NERFINISHED

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: Cieszyn | Statement: [Cieszyn County, capital, Cieszyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cieszyn
Context triple: [Cieszyn County, capital, Cieszyn]
  • A. Cieszyn chosen
    Cieszyn is a historic town in southern Poland on the Olza River, known for its shared Polish-Czech heritage and well-preserved old town.
  • B. Cieszyn Silesia
    Cieszyn Silesia is a historical and ethnically diverse borderland region centered around the city of Cieszyn, spanning areas of present-day Poland and the Czech Republic.
  • C. Chorzów
    Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
  • D. Świdnica
    Świdnica is a historic town in southwestern Poland known for its well-preserved medieval architecture and the UNESCO-listed Church of Peace.
  • E. Kluczbork
    Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d7bdfb57a88190836b743e2825feca completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97e1edcdc8190a702c2a5ea58cc67 completed April 10, 2026, 10:47 p.m.
Created at: April 9, 2026, 5:43 p.m.