Triple

T15250989
Position Surface form Disambiguated ID Type / Status
Subject Labské pískovce E364516 entity
Predicate near P350 FINISHED
Object Hřensko E1122808 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: Hřensko | Statement: [Labské pískovce, near, Hřensko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hřensko
Context triple: [Labské pískovce, near, Hřensko]
  • A. Hřensko chosen
    Hřensko is a small Czech village in the Bohemian Switzerland National Park, known as a gateway to sandstone rock formations and popular hiking destinations near the German border.
  • B. Harrachov
    Harrachov is a Czech mountain town in the Krkonoše range known as a major ski and winter sports resort near the Polish border.
  • C. Vyhne
    Vyhne is a historic village in central Slovakia known for its former mining activities, spa traditions, and scenic mountainous surroundings.
  • D. Husinec
    Husinec is a small Czech town best known as the birthplace of the religious reformer Jan Hus.
  • E. Hronov
    Hronov is a small town in the Hradec Králové Region of the Czech Republic, known as the birthplace of writer Alois Jirásek and for its traditional cultural events.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f728648190b2c86e4528542b65 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff219294d48190a4b6754aa107b155 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:13 a.m.