Triple

T4495706
Position Surface form Disambiguated ID Type / Status
Subject Spišská Nová Ves E100688 entity
Predicate hasTwinTown P919 FINISHED
Object Cieszyn E304189 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: Cieszyn | Statement: [Spišská Nová Ves, hasTwinTown, Cieszyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cieszyn
Context triple: [Spišská Nová Ves, hasTwinTown, 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. Wałbrzych
    Wałbrzych is a city in southwestern Poland known for its industrial heritage, historic coal mining, and proximity to the Sudetes mountains.
  • 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_69bd43cdf15081909a4fa2585ff63b3e completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd56bde14c819091d42839a46291d0 completed March 20, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8f2f8624c819090b3e197ec1c8891 completed March 29, 2026, 9:38 a.m.
Created at: March 20, 2026, 1 p.m.