Triple

T10694293
Position Surface form Disambiguated ID Type / Status
Subject Offenburg E252092 entity
Predicate locatedOn P40 FINISHED
Object Kinzig River E112852 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: Kinzig River | Statement: [Offenburg, locatedOn, Kinzig River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kinzig River
Context triple: [Offenburg, locatedOn, Kinzig River]
  • A. Kinzig chosen
    The Kinzig is a river in southwestern Germany that flows through the Black Forest region before joining the Rhine.
  • B. Neckar
    The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
  • C. 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.
  • D. Regnitz
    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.
  • E. Wiese River
    The Wiese River is a tributary of the Rhine flowing through parts of Germany and Switzerland, including the municipality of Riehen near Basel.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd39c3788190bb7cd0acf8b6efdd completed April 9, 2026, 1:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e6968aec8190a9d1e51ac7e87853 completed April 21, 2026, 2:53 a.m.
Created at: April 8, 2026, 9:11 p.m.