Triple

T20099382
Position Surface form Disambiguated ID Type / Status
Subject Dornbirn E496491 entity
Predicate hasTwinTown P919 FINISHED
Object Toruń 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: Toruń | Statement: [Dornbirn, hasTwinTown, Toruń]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toruń
Context triple: [Dornbirn, hasTwinTown, Toruń]
  • A. Toruń chosen
    Toruń is a historic city in northern Poland, renowned for its well-preserved medieval Old Town and as the birthplace of astronomer Nicolaus Copernicus.
  • B. Bydgoszcz
    Bydgoszcz is a major city in northern Poland known as an important economic, cultural, and academic center on the Brda and Vistula rivers.
  • C. Olsztyn
    Olsztyn is a historic city in northern Poland known for its medieval architecture, lakes, and role as the capital of the Warmian-Masurian Voivodeship.
  • D. Opole
    Opole is a historic city in southwestern Poland, known as one of the country’s oldest urban centers and a regional cultural hub.
  • E. Poznań
    Poznań is a historic and economically significant city in western Poland, known for its medieval Old Town, role as an early center of Polish statehood, and status as a major academic and industrial hub.
  • 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6666f2298819089659f13556ca305 completed April 20, 2026, 5:46 p.m.
Created at: April 11, 2026, 11:26 p.m.