Triple

T15048191
Position Surface form Disambiguated ID Type / Status
Subject 2002 European floods E379285 entity
Predicate mainRiverAffected P75568 FINISHED
Object Isar E66587 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: Isar | Statement: [2002 European floods, mainRiverAffected, Isar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isar
Context triple: [2002 European floods, mainRiverAffected, Isar]
  • A. Isar chosen
    The Isar is a major river in the Austrian and German Alps that flows through cities such as Munich before joining the Danube.
  • B. Isar
    Isar is a structured, human-readable proof language designed for writing formal proofs within the Isabelle interactive theorem prover.
  • C. Isar valley
    The Isar valley is a scenic river valley in Bavaria, Germany, known for its picturesque landscapes, forests, and traditional towns along the Isar River.
  • D. Aichach
    Aichach is a town in Bavaria, Germany, known in part for its prison where several Nazi war criminals, including Ilse Koch, were held and died.
  • E. Hadern
    Hadern is a borough in the southwest of Munich, Germany, known for its residential character and the large Waldfriedhof cemetery.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda8e64e48190873104a02a676ff3 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9de73614819098b7a88624407d0e completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 3 a.m.