Triple

T446093
Position Surface form Disambiguated ID Type / Status
Subject Vienna E7023 entity
Predicate locatedOnRiver P165 FINISHED
Object Danube E12683 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: Danube | Statement: [Vienna, locatedOnRiver, Danube]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danube
Context triple: [Vienna, locatedOnRiver, Danube]
  • A. Danube chosen
    The Danube is one of Europe's longest and most historically significant rivers, flowing from Germany to the Black Sea and passing through numerous Central and Eastern European countries.
  • B. Elbe
    The Elbe is one of Central Europe's major rivers, flowing from the Czech Republic through Germany to the North Sea and serving as an important waterway for transport, industry, and agriculture.
  • C. Tisza
    The Tisza is one of Central Europe's significant rivers, flowing through several countries including Hungary before joining the Danube.
  • D. Rhine
    The Rhine is one of Europe's most important rivers, historically serving as a vital trade route and cultural boundary from the Alps through Germany to the North Sea.
  • E. Vistula River
    The Vistula River is Poland’s longest and most important river, flowing from the Carpathian Mountains to the Baltic Sea and passing through major cities such as Kraków and Warsaw.
  • 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_69a2e7e4676c81909ea0dbdecac0687c completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ef479ec08190a659eead6eb0d4d0 completed Feb. 28, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4777ac3748190989ab6a9565d2c8a completed March 1, 2026, 5:29 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.