Triple

T10168520
Position Surface form Disambiguated ID Type / Status
Subject Nymburk E235268 entity
Predicate hasRailwayStation P918 FINISHED
Object Nymburk město E235268 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: Nymburk město | Statement: [Nymburk, hasRailwayStation, Nymburk město]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nymburk město
Context triple: [Nymburk, hasRailwayStation, Nymburk město]
  • A. Nymburk chosen
    Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe River.
  • B. Rumburk
    Rumburk is a small historic town in the northern Czech Republic, near the German border, known for its Baroque architecture and location in the Šluknov Hook region.
  • C. Jičín
    Jičín is a historic town in the Czech Republic known for its well-preserved medieval center and association with the fairy-tale character Rumcajs.
  • D. Příbram
    Příbram is a historic mining town in the Czech Republic known for its silver and uranium mining heritage and the Svatá Hora pilgrimage site.
  • E. Moravské Budějovice
    Moravské Budějovice is a small historic town in the Czech Republic known for its traditional architecture and regional cultural heritage.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec6f64a48190883aefce58a65ca6 completed April 2, 2026, 4:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d300ebacb88190850cf2242309b6ba completed April 6, 2026, 12:40 a.m.
Created at: March 30, 2026, 9:10 p.m.