Triple

T19481598
Position Surface form Disambiguated ID Type / Status
Subject Count Vertigo E487397 entity
Predicate homeCountry P1083 FINISHED
Object Vlatava E108852 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: Vlatava | Statement: [Count Vertigo, homeCountry, Vlatava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vlatava
Context triple: [Count Vertigo, homeCountry, Vlatava]
  • A. Vltava River chosen
    The Vltava River is the longest river in the Czech Republic, flowing through the capital city of Prague and serving as a central feature of its landscape and history.
  • B. Vukosava
    Vukosava is known in Serbian medieval history as the mother of Saint Prince Lazar, the revered ruler and martyr of the Battle of Kosovo.
  • C. West Morava
    West Morava is a major river in central Serbia that serves as one of the two principal headwaters of the Velika Morava.
  • D. Vltavská
    Vltavská is a Prague Metro station on Line C, located near the Vltava River in the Holešovice area of Prague, Czech Republic.
  • E. Velika Morava
    Velika Morava is a major river in central Serbia formed by the confluence of the West and South Morava, flowing northward before joining the Danube.
  • 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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e634393b8081909f5e4c38b2f1a9b7 completed April 20, 2026, 2:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07ea287a948190a7578138ceb9724f completed May 16, 2026, 3:53 a.m.
Created at: April 10, 2026, 1:39 p.m.