Triple

T6945429
Position Surface form Disambiguated ID Type / Status
Subject Schwielowsee E160785 entity
Predicate hasRiver P165 FINISHED
Object Havel E34243 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: Havel | Statement: [Schwielowsee, hasRiver, Havel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Havel
Context triple: [Schwielowsee, hasRiver, 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. Haveltermade
    Haveltermade is a residential district of the Dutch city of Meppel in the province of Drenthe.
  • E. Jan Stráský
    Jan Stráský was a Czech politician who served in top governmental roles during the final years of Czechoslovakia and later in the Czech Republic.
  • 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_69c68850419081909fb426b8f5a304c7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da8a65c48190b6862fc60f6c7f7a completed March 27, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769fd908c81908d92ff4cd79b76c0 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:28 p.m.