Triple

T12600282
Position Surface form Disambiguated ID Type / Status
Subject Bergisches Land E300838 entity
Predicate contains P35 FINISHED
Object Lindlar
Lindlar is a municipality in western Germany’s North Rhine-Westphalia, known for its rural character and location within the hilly Bergisches Land region.
 E991903 NE FINISHED

How this triple was built (4 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: Lindlar | Statement: [Bergisches Land, contains, Lindlar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lindlar
Context triple: [Bergisches Land, contains, Lindlar]
  • A. Eschenmoser
    Eschenmoser is a Swiss surname most notably associated with Albert Eschenmoser, a prominent organic chemist known for his pioneering work in the synthesis of complex natural products and studies on the origin of life.
  • B. Gomberg
    Gomberg is a surname most notably associated with American screenwriter and producer Sy Gomberg.
  • C. Beckmann
    Beckmann is a German surname most famously associated with the Expressionist painter Max Beckmann.
  • D. Coumet
    Coumet is a French surname most notably borne by Jérôme Coumet, a contemporary French politician.
  • E. Treuttel et Würtz
    Treuttel et Würtz was a prominent 19th-century European publishing and bookselling firm known for issuing scholarly and scientific works.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lindlar
Triple: [Bergisches Land, contains, Lindlar]
Generated description
Lindlar is a municipality in western Germany’s North Rhine-Westphalia, known for its rural character and location within the hilly Bergisches Land region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lindlar
Target entity description: Lindlar is a municipality in western Germany’s North Rhine-Westphalia, known for its rural character and location within the hilly Bergisches Land region.
  • A. Eschenmoser
    Eschenmoser is a Swiss surname most notably associated with Albert Eschenmoser, a prominent organic chemist known for his pioneering work in the synthesis of complex natural products and studies on the origin of life.
  • B. Gomberg
    Gomberg is a surname most notably associated with American screenwriter and producer Sy Gomberg.
  • C. Beckmann
    Beckmann is a German surname most famously associated with the Expressionist painter Max Beckmann.
  • D. Coumet
    Coumet is a French surname most notably borne by Jérôme Coumet, a contemporary French politician.
  • E. Treuttel et Würtz
    Treuttel et Würtz was a prominent 19th-century European publishing and bookselling firm known for issuing scholarly and scientific works.
  • F. None of above. chosen

Provenance (5 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954d1f6ac8190ab21ca7bcbc80129 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ec92c6c8190bd2d193e70940407 completed May 2, 2026, 8:30 p.m.
NEDg Description generation batch_69f65faf33e0819092df07a5fa98cb73 completed May 2, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_69f66036f520819098af75cd5578d573 completed May 2, 2026, 8:36 p.m.
Created at: April 9, 2026, 5:09 p.m.