Triple

T16199693
Position Surface form Disambiguated ID Type / Status
Subject Line B (Prague Metro) E393164 entity
Predicate hasTerminus P388 FINISHED
Object Zličín E393165 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: Zličín | Statement: [Line B (Prague Metro), hasTerminus, Zličín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zličín
Context triple: [Line B (Prague Metro), hasTerminus, Zličín]
  • A. Zličín chosen
    Zličín is a district in the western part of Prague that serves as a key transport hub and terminus of a Prague Metro line.
  • B. Dubí
    Dubí is a small spa town in the Ústí nad Labem Region of the Czech Republic, known for its porcelain production and location in the Ore Mountains near the German border.
  • C. Zruč nad Sázavou
    Zruč nad Sázavou is a small historic town in the Central Bohemian Region of the Czech Republic, known for its riverside setting, castle, and former industrial (especially shoe-making) tradition.
  • D. Libeň
    Libeň is a district in Prague known for its mix of residential areas, industrial heritage, and major venues such as the O2 Arena.
  • E. Zbyhněv
    Zbyhněv is a given name, likely a variant or regional form of the Slavic name Zbigniew.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222de2db481908471b9c73d444607 completed April 17, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00456f2ba481909f243ab2c4619623 completed May 10, 2026, 8:44 a.m.
Created at: April 10, 2026, 5:03 a.m.