Triple

T17812633
Position Surface form Disambiguated ID Type / Status
Subject Haselhorst E444749 entity
Predicate hasRiverBank P8340 FINISHED
Object Havel NE NERFINISHED

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: Havel | Statement: [Haselhorst, hasRiverBank, Havel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Havel
Context triple: [Haselhorst, hasRiverBank, Havel]
  • A. Havel chosen
    The Havel is a river in northeastern Germany that flows through Berlin and Brandenburg before joining the Elbe.
  • B. Václav Havel
    Václav Havel was a Czech playwright, dissident, and statesman who became the last president of Czechoslovakia and the first president of the Czech Republic, symbolizing the country’s transition from communism to democracy.
  • C. Havlíček
    Havlíček is a Czech surname most famously associated with basketball Hall of Famer John Havlicek and several notable Czech cultural and public figures.
  • D. Jiří Šlitr
    Jiří Šlitr was a Czech composer, pianist, singer, and actor best known for his influential work in Czech popular music and theater during the 1960s, particularly in collaboration with Jiří Suchý at the Semafor Theatre.
  • E. Miroslav Hájek
    Miroslav Hájek was a Czech film editor known for his work on notable Czechoslovak New Wave films.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4887c63608190b29a407cabff0bc5 completed April 19, 2026, 7:47 a.m.
Created at: April 10, 2026, 10:14 a.m.