Triple

T4106635
Position Surface form Disambiguated ID Type / Status
Subject Daimler AG E88466 entity
Predicate brand P1500 FINISHED
Object Setra
Setra is a German brand of premium coaches and buses known for its high-quality engineering and comfort, produced by Daimler AG.
 E412320 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: Setra | Statement: [Daimler AG, brand, Setra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Setra
Context triple: [Daimler AG, brand, Setra]
  • A. Suhre
    The Suhre is a river in Switzerland that flows through the cantons of Lucerne and Aargau before joining the Aare.
  • B. Geva
    Geva is a surname most notably associated with Tamara Geva, a Russian-American actress, dancer, and choreographer.
  • C. Gonda
    Gonda is a city in the Indian state of Uttar Pradesh, known for its agricultural economy and proximity to the Ghaghara River.
  • D. Sutrio
    Sutrio is a small village in Italy’s Friuli-Venezia Giulia region, known as a traditional Alpine community and a base for accessing the nearby Monte Zoncolan ski and cycling area.
  • E. Cosia
    Cosia is a small river in northern Italy that flows through the city of Como before emptying into Lake Como.
  • 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: Setra
Triple: [Daimler AG, brand, Setra]
Generated description
Setra is a German brand of premium coaches and buses known for its high-quality engineering and comfort, produced by Daimler AG.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Setra
Target entity description: Setra is a German brand of premium coaches and buses known for its high-quality engineering and comfort, produced by Daimler AG.
  • A. Suhre
    The Suhre is a river in Switzerland that flows through the cantons of Lucerne and Aargau before joining the Aare.
  • B. Geva
    Geva is a surname most notably associated with Tamara Geva, a Russian-American actress, dancer, and choreographer.
  • C. Gonda
    Gonda is a city in the Indian state of Uttar Pradesh, known for its agricultural economy and proximity to the Ghaghara River.
  • D. Sutrio
    Sutrio is a small village in Italy’s Friuli-Venezia Giulia region, known as a traditional Alpine community and a base for accessing the nearby Monte Zoncolan ski and cycling area.
  • E. Cosia
    Cosia is a small river in northern Italy that flows through the city of Como before emptying into Lake Como.
  • 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_69aed9484fb881909146f4c772ad277c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af019c7a3c8190a503ce80e87dc3b3 completed March 9, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b7f88948190b87242e706a488c0 completed March 14, 2026, 2:06 p.m.
NEDg Description generation batch_69b56c0a3b1c81908ae4c630c6881c1c completed March 14, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_69b56c94df3481908d2f4a3976fb775b completed March 14, 2026, 2:11 p.m.
Created at: March 9, 2026, 3:40 p.m.