Triple

T4116282
Position Surface form Disambiguated ID Type / Status
Subject State of Berlin E90298 entity
Predicate containsRiver 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: [State of Berlin, containsRiver, Havel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Havel
Context triple: [State of Berlin, containsRiver, 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 Novotný
    Jiří Novotný is a Czech professional ice hockey center known for his NHL career and international play for the Czech national team.
  • E. Vojtech
    Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • 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_69aed95c080881908125e30c5dcdc6f8 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af01f1e2e08190a6b73d7674c34e88 completed March 9, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b90054081908a51c366c6fe51d7 completed March 14, 2026, 2:07 p.m.
Created at: March 9, 2026, 3:41 p.m.