Triple

T8848407
Position Surface form Disambiguated ID Type / Status
Subject Naumburg E210567 entity
Predicate hasTwinTown P919 FINISHED
Object Česká Lípa E527740 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: Česká Lípa | Statement: [Naumburg, hasTwinTown, Česká Lípa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Česká Lípa
Context triple: [Naumburg, hasTwinTown, Česká Lípa]
  • A. Česká Lípa chosen
    Česká Lípa is a town in the Liberec Region of the Czech Republic, known as a regional center near the Ploučnice River with historical roots dating back to the Middle Ages.
  • B. Český Brod
    Český Brod is a historic town in the Central Bohemian Region of the Czech Republic, known for its medieval architecture and role as a former royal town on important trade routes.
  • C. Gottwaldov
    Gottwaldov is the former name (1949–1990) of the Czech industrial city now known as Zlín, historically associated with the Baťa shoe company.
  • D. Ústí nad Labem
    Ústí nad Labem is an industrial city in the north of the Czech Republic, known as a major transport hub and river port in the Bohemian region.
  • E. Teplice
    Teplice is a historic spa city in the north of the Czech Republic, renowned for its thermal springs and long tradition of balneotherapy.
  • 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_69ca838967bc8190b46c3c80a2887ea4 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60aa6db0819097c3257499200afc completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b54de2cc8190b14e3e726b4e9384 completed April 5, 2026, 7:17 p.m.
Created at: March 30, 2026, 6:49 p.m.