Triple

T791847
Position Surface form Disambiguated ID Type / Status
Subject Alps E16930 entity
Predicate sourceOf P409 FINISHED
Object Rhine E13461 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: Rhine | Statement: [Alps, sourceOf, Rhine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rhine
Context triple: [Alps, sourceOf, Rhine]
  • A. Rhine chosen
    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.
  • B. Rhens
    Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
  • C. Weser
    The Weser is a major river in northwestern Germany that flows through several federal states before emptying into the North Sea.
  • D. Neckar
    The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
  • E. Meuse
    The Meuse is a major European river flowing through France, Belgium, and the Netherlands, historically important for transport, trade, and the development of surrounding regions.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a798c7608190b9c79c52a1fe0859 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3b978de4819083b117ee3a6cb8c1 completed March 7, 2026, 2:52 p.m.
Created at: March 1, 2026, 7:38 p.m.