Triple

T644000
Position Surface form Disambiguated ID Type / Status
Subject Mercedes-Benz E11202 entity
Predicate brandSegment P16877 FINISHED
Object EQ
EQ is Mercedes-Benz’s dedicated sub-brand for electric vehicles and related technologies, representing the company’s push into premium, battery-powered mobility.
 E80322 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: EQ | Statement: [Mercedes-Benz, brandSegment, EQ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EQ
Context triple: [Mercedes-Benz, brandSegment, EQ]
  • A. EK
    EK is the commonly used abbreviation for the First Chamber of the Austrian Parliament (Erste Kammer).
  • B. QR
    QR is the two-letter IATA airline designator assigned to Qatar Airways, the flag carrier of Qatar.
  • C. LUV
    LUV is the stock ticker symbol for Southwest Airlines, a major U.S. low-cost airline known for its extensive domestic route network and no-frills service model.
  • D. Este
    Este is an ancient town in northern Italy notable as a key center of the Venetic civilization and culture.
  • E. Crystal
    Crystal is a feminine given name often associated with clarity and beauty, derived from the English word for clear, transparent mineral or glass.
  • 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: EQ
Triple: [Mercedes-Benz, brandSegment, EQ]
Generated description
EQ is Mercedes-Benz’s dedicated sub-brand for electric vehicles and related technologies, representing the company’s push into premium, battery-powered mobility.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EQ
Target entity description: EQ is Mercedes-Benz’s dedicated sub-brand for electric vehicles and related technologies, representing the company’s push into premium, battery-powered mobility.
  • A. EK
    EK is the commonly used abbreviation for the First Chamber of the Austrian Parliament (Erste Kammer).
  • B. QR
    QR is the two-letter IATA airline designator assigned to Qatar Airways, the flag carrier of Qatar.
  • C. LUV
    LUV is the stock ticker symbol for Southwest Airlines, a major U.S. low-cost airline known for its extensive domestic route network and no-frills service model.
  • D. Este
    Este is an ancient town in northern Italy notable as a key center of the Venetic civilization and culture.
  • E. Crystal
    Crystal is a feminine given name often associated with clarity and beauty, derived from the English word for clear, transparent mineral or glass.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a515ceb081908c064b2082047c0f completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5778faa788190ac246d6cd6b983f4 completed March 2, 2026, 11:42 a.m.
NEDg Description generation batch_69a57806b6148190a56a1ed535bb3a65 completed March 2, 2026, 11:44 a.m.
NED2 Entity disambiguation (via description) batch_69a5785996748190ae7761d190bbd35f completed March 2, 2026, 11:45 a.m.
Created at: March 1, 2026, 7:36 p.m.