Triple

T1456375
Position Surface form Disambiguated ID Type / Status
Subject Cieszyn Silesia E31409 entity
Predicate hasMajorCity P316 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: [Cieszyn Silesia, hasMajorCity, Cieszyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cieszyn
Context triple: [Cieszyn Silesia, hasMajorCity, 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. Przemyśl
    Przemyśl is a historic city in southeastern Poland near the Ukrainian border, known for its strategic location, multicultural heritage, and well-preserved fortifications.
  • E. Bielsko-Biała
    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.
  • 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c598b30c8190b87207adf608b89a completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b05570cd488190bd9ce6b3a854a427 completed March 10, 2026, 5:31 p.m.
Created at: March 1, 2026, 8 p.m.