Triple

T23215844
Position Surface form Disambiguated ID Type / Status
Subject Troisdorf E580736 entity
Predicate locatedOn P40 FINISHED
Object River Sieg NE NERFINISHED

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: River Sieg | Statement: [Troisdorf, locatedOn, River Sieg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: River Sieg
Context triple: [Troisdorf, locatedOn, River Sieg]
  • A. river Sieg chosen
    The river Sieg is a tributary of the Rhine in western Germany, flowing through North Rhine-Westphalia and Rhineland-Palatinate and giving its name to several nearby towns.
  • B. River Wiese
    The River Wiese is a river in southwestern Germany and northwestern Switzerland that flows through the Black Forest region before joining the Rhine near Basel.
  • C. Möhne River
    The Möhne River is a waterway in North Rhine-Westphalia, Germany, known for the large reservoir and hydroelectric infrastructure associated with the Möhne Dam.
  • D. Schwalm River
    The Schwalm River is a waterway in the German state of Hesse that lends its name to the surrounding Schwalm-Eder region.
  • E. Rheine
    Rheine is a German city in the state of North Rhine-Westphalia, known for its historical town center and location along the River Ems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f191646c548190a3f7150f0c253dc1 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.