Triple

T940683
Position Surface form Disambiguated ID Type / Status
Subject Crossing of the Rhine E20297 entity
Predicate riverCrossed P416 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: [Crossing of the Rhine, riverCrossed, Rhine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rhine
Context triple: [Crossing of the Rhine, riverCrossed, 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
    Meuse is a department in northeastern France known for its rural landscapes and significant World War I battlefields, including Verdun.
  • 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_69a493b0270c81909e6c9ce310f6aa55 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b38cc6888190b1d9043ec8fbcbc3 completed March 1, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc5ff51c48190ab9b096d9d885d8f completed March 8, 2026, 12:42 a.m.
Created at: March 1, 2026, 7:40 p.m.