Triple

T2982991
Position Surface form Disambiguated ID Type / Status
Subject Ruhr E80553 entity
Predicate hasTributary P415 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: [Ruhr, hasTributary, Möhne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Möhne
Context triple: [Ruhr, hasTributary, 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. 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.
  • C. Lippe
    Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • 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. Roer
    The Roer is a river in Western Europe that flows through parts of Belgium, Germany, and the Netherlands before joining the Meuse.
  • 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_69ad8b15f6ac8190be5fd16a33edcb4f completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99a1ed44819085ae6d39943db1d9 completed March 8, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fadc46e8819095ebcb23e1da9947 completed March 14, 2026, 6:06 a.m.
Created at: March 8, 2026, 2:58 p.m.