Triple

T6032226
Position Surface form Disambiguated ID Type / Status
Subject Hochsauerlandkreis E134331 entity
Predicate hasRiver P165 FINISHED
Object Möhne E300533 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: Möhne | Statement: [Hochsauerlandkreis, hasRiver, Möhne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Möhne
Context triple: [Hochsauerlandkreis, hasRiver, Möhne]
  • A. Möhne River chosen
    The Möhne River is a waterway in North Rhine-Westphalia, Germany, known for the large reservoir and hydroelectric infrastructure associated with the Möhne Dam.
  • B. Schwalm River
    The Schwalm River is a waterway in the German state of Hesse that lends its name to the surrounding Schwalm-Eder region.
  • C. 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.
  • D. Lippe
    The Lippe is a river in western Germany that flows through North Rhine-Westphalia and is a right-bank tributary of the Rhine.
  • E. Lippe
    Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • 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_69c0087515148190a97475d412563865 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056b0a8d081909035e2e85e851ca1 completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c113855ad08190b9ff826a2f39c356 completed March 23, 2026, 10:18 a.m.
Created at: March 22, 2026, 4:08 p.m.