Triple

T10629743
Position Surface form Disambiguated ID Type / Status
Subject Möhnesee E250420 entity
Predicate locatedOn P40 FINISHED
Object Möhne River 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 River | Statement: [Möhnesee, locatedOn, Möhne River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Möhne River
Context triple: [Möhnesee, locatedOn, Möhne River]
  • 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. Fulda River
    The Fulda River is a major river in central Germany that flows through the state of Hesse and joins the Werra River at Hann. Münden to form the Weser.
  • D. 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.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df92f8388190a8bcff96809d8eb4 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69dff76eef4c8190b4fe681a9431207d completed April 15, 2026, 8:39 p.m.
Created at: April 8, 2026, 9 p.m.