Triple

T10892337
Position Surface form Disambiguated ID Type / Status
Subject Steinfurt (district) E257209 entity
Predicate contains P35 FINISHED
Object Emsdetten E850475 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: Emsdetten | Statement: [Steinfurt (district), contains, Emsdetten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emsdetten
Context triple: [Steinfurt (district), contains, Emsdetten]
  • A. Emsdetten chosen
    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.
  • B. 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.
  • C. Ems
    The Ems is a river in northwestern Germany that flows through several states before emptying into the North Sea.
  • 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. 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75206354881908b148f2df3938513 completed April 9, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43ee693048190a8c7ecdf8724d3ec completed May 1, 2026, 5:49 a.m.
Created at: April 8, 2026, 9:21 p.m.