Triple

T6993961
Position Surface form Disambiguated ID Type / Status
Subject Dortmund E162155 entity
Predicate river P165 FINISHED
Object Emscher E524728 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: Emscher | Statement: [Dortmund, river, Emscher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emscher
Context triple: [Dortmund, river, Emscher]
  • A. Emscher chosen
    The Emscher is a river in Germany’s Ruhr industrial region, historically known for its heavy pollution and extensive canalization before major ecological restoration efforts.
  • B. Ruhr
    The Ruhr is a river in western Germany that flows through the Ruhr industrial region before joining the Rhine.
  • C. Lippe
    The Lippe is a river in western Germany that flows through North Rhine-Westphalia and is a right-bank tributary of the Rhine.
  • D. Lippe
    Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • E. Rhein II
    Rhein II is a large-scale color photograph by German visual artist Andreas Gursky, renowned for its minimalist depiction of the Rhine River and for once being the most expensive photograph ever sold at auction.
  • 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbeaa88c8190a49f8504c1793e1f completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b8b9a0e881909ee8f92ecb6fef66 completed March 28, 2026, 11:17 a.m.
Created at: March 27, 2026, 2:32 p.m.