Triple

T2663725
Position Surface form Disambiguated ID Type / Status
Subject Plzeň Region E54782 entity
Predicate hasCity P316 FINISHED
Object Domažlice E295569 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: Domažlice | Statement: [Plzeň Region, hasCity, Domažlice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Domažlice
Context triple: [Plzeň Region, hasCity, Domažlice]
  • A. Domažlice chosen
    Domažlice is a historic town in the western Czech Republic known for its well-preserved medieval center and rich Chodové folk traditions.
  • B. Říčany
    Říčany is a town in the Czech Republic, located just southeast of Prague and known as a popular residential and commuter suburb with historical roots.
  • C. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • D. Sedlčany
    Sedlčany is a small historic town in the Czech Republic known for its traditional cheese production and location on the Mastník River.
  • E. Znojmo
    Znojmo is a historic town in the South Moravian Region of the Czech Republic, known for its medieval architecture, wine production, and strategic position near the Austrian border.
  • 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd96b9f1c8190a8a9460ca88a9aaf completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108c261e881909fd7800880c0faf1 completed March 11, 2026, 6:16 a.m.
Created at: March 6, 2026, 9:54 p.m.