Triple

T35758115
Position Surface form Disambiguated ID Type / Status
Subject Mercedes-Benz W140 E1033499 entity
Predicate coupéModelName P55902 FINISHED
Object CL-Class
The CL-Class is Mercedes-Benz's line of full-size luxury grand tourer coupés, known for combining high performance with advanced comfort and technology features.
 E2154609 NE FINISHED

How this triple was built (3 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: CL-Class | Statement: [Mercedes-Benz W140, coupéModelName, CL-Class]
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: CL-Class
Triple: [Mercedes-Benz W140, coupéModelName, CL-Class]
Generated description
The CL-Class is Mercedes-Benz's line of full-size luxury grand tourer coupés, known for combining high performance with advanced comfort and technology features.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: coupéModelName
Context triple: [Mercedes-Benz W140, coupéModelName, CL-Class]
  • A. carModel
    Indicates the specific model designation of a car within a particular make or brand.
  • B. coupeIntroductionYear
    Indicates the year in which a coupe model was first introduced.
  • C. racingModel
    Indicates that one entity is a specific model or version designed or configured for racing in relation to another entity.
  • D. vehicleName chosen
    Indicates the specific name or designation assigned to a vehicle.
  • E. firstModelYearNameplate
    Indicates the specific model year in which a particular nameplate (vehicle model designation) was first introduced.
  • F. None of above.

Provenance (6 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_69f76e1262f48190a313318665acc189 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa699d68819081ed363931894ab3 completed May 3, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3885f897a08190badf29b5cc6dba37 completed June 22, 2026, 12:46 a.m.
NEDg Description generation batch_6a3887948e148190873b6efc5735127b completed June 22, 2026, 12:53 a.m.
NED2 Entity disambiguation (via description) batch_6a388849bf348190ba71468323566c56 completed June 22, 2026, 12:56 a.m.
PD Predicate disambiguation batch_69f7a8d219f8819081dc4ce3c83ca0cb completed May 3, 2026, 7:58 p.m.
Created at: May 3, 2026, 4:06 p.m.