Triple

T10347065
Position Surface form Disambiguated ID Type / Status
Subject Český Těšín E243777 entity
Predicate locatedOpposite P3232 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: [Český Těšín, locatedOpposite, Cieszyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cieszyn
Context triple: [Český Těšín, locatedOpposite, 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 (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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9251654819080d1e3f0ed4ee9d3 completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0ce0a508190a2f44cbe812b5f17 completed May 3, 2026, 3:28 a.m.
Created at: April 6, 2026, 11:56 a.m.