Triple

T6623113
Position Surface form Disambiguated ID Type / Status
Subject Leszno E149724 entity
Predicate hasTwinTown P919 FINISHED
Object Nitra E324821 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: Nitra | Statement: [Leszno, hasTwinTown, Nitra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nitra
Context triple: [Leszno, hasTwinTown, Nitra]
  • A. Nitra chosen
    Nitra is one of the oldest cities in Slovakia, known for its historic castle, early Christian heritage, and role as a cultural and academic center.
  • B. Vác
    Vác is a historic town on the Danube in northern Hungary, known for its Baroque architecture and role as a regional cultural and religious center.
  • C. Vsetín
    Vsetín is a town in the eastern Czech Republic known as an industrial and cultural center of the Moravian Wallachia region.
  • D. Karviná
    Karviná is an industrial city in the Moravian-Silesian Region of the Czech Republic, historically part of Cieszyn Silesia and known for its coal mining heritage.
  • E. Lovech
    Lovech is a historic city in north-central Bulgaria, known for its medieval fortress, picturesque old town, and important role during the Second Bulgarian Empire.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af7decb08190a7b1ddb95e534a6a completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eee8740881908b4fafb12db6b7f3 completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 1:58 p.m.