Triple

T22793621
Position Surface form Disambiguated ID Type / Status
Subject Westfalen E564180 entity
Predicate traversedByRiver P165 FINISHED
Object Ems 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: Ems | Statement: [Westfalen, traversedByRiver, Ems]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ems
Context triple: [Westfalen, traversedByRiver, Ems]
  • A. Ems
    Ems is a historic spa town in present-day Germany, renowned for its mineral springs and 19th-century status as a fashionable European resort.
  • B. Ems chosen
    The Ems is a river in northwestern Germany that flows through several states before emptying into the North Sea.
  • C. Emsdetten
    Emsdetten is a town in the district of Steinfurt in North Rhine-Westphalia, Germany, known for its textile industry heritage and location along the Ems River.
  • D. Emst
    Emst is a small village in the Dutch province of Gelderland, known as part of the municipality of Epe in the Veluwe region.
  • E. Rhens
    Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
  • 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_69e2458185f88190b0045227ee420411 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17cd751f081909c7907c96c9906ea completed April 29, 2026, 3:36 a.m.
Created at: April 17, 2026, 3:30 p.m.