Triple

T10076252
Position Surface form Disambiguated ID Type / Status
Subject Stadt Fürth E213765 entity
Predicate hasRiver P165 FINISHED
Object Regnitz E124915 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: Regnitz | Statement: [Stadt Fürth, hasRiver, Regnitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Regnitz
Context triple: [Stadt Fürth, hasRiver, Regnitz]
  • A. Regnitz chosen
    The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
  • B. Saale
    The Saale is a major river in central Germany that flows through the states of Thuringia, Saxony-Anhalt, and Bavaria before joining the Elbe.
  • C. Wupper
    The Wupper is a river in North Rhine-Westphalia, Germany, known for flowing through the industrial city of Wuppertal and its surrounding region.
  • D. Neckar
    The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
  • E. Würm River
    The Würm River is a small river in Bavaria, Germany, known for flowing north from Lake Starnberg through towns such as Gauting and Starnberg before joining the Amper River.
  • 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_69ca839add308190b57d53b4ec21f2d0 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd0190d808190847ea0fa401ef06c completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69e343941ae481909489cf7a4abdba68 completed April 18, 2026, 8:40 a.m.
Created at: March 30, 2026, 8:59 p.m.