Triple

T1754701
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen Passat E38524 entity
Predicate hasGeneration P455 FINISHED
Object B2
B2 is the second-generation Volkswagen Passat, produced in the early 1980s and known for its more angular design and expanded body style options compared to its predecessor.
 E196136 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: B2 | Statement: [Volkswagen Passat, hasGeneration, B2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: B2
Context triple: [Volkswagen Passat, hasGeneration, B2]
  • A. B
    B is the designation of one of the main lines of the Paris RER commuter rail network, serving a major north–south axis through the Île-de-France region.
  • B. B
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • C. B
    B is an early systems programming language developed at Bell Labs that served as a direct precursor to the C programming language.
  • D. B
    B is a New York City Subway service that runs on the IND Sixth Avenue Line, providing local and express service through Manhattan and Brooklyn.
  • E. BA
    BA is the commonly used abbreviation for the British Academy, the United Kingdom’s national academy for the humanities and social sciences.
  • 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: B2
Triple: [Volkswagen Passat, hasGeneration, B2]
Generated description
B2 is the second-generation Volkswagen Passat, produced in the early 1980s and known for its more angular design and expanded body style options compared to its predecessor.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: B2
Target entity description: B2 is the second-generation Volkswagen Passat, produced in the early 1980s and known for its more angular design and expanded body style options compared to its predecessor.
  • A. B
    B is the designation of one of the main lines of the Paris RER commuter rail network, serving a major north–south axis through the Île-de-France region.
  • B. B
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • C. B
    B is an early systems programming language developed at Bell Labs that served as a direct precursor to the C programming language.
  • D. B
    B is a New York City Subway service that runs on the IND Sixth Avenue Line, providing local and express service through Manhattan and Brooklyn.
  • E. BA
    BA is the commonly used abbreviation for the British Academy, the United Kingdom’s national academy for the humanities and social sciences.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa641841748190ad05cac4a27cced9 completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0e84c1c8190917edf14003cba81 completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada1a401548190af00bae3b89e46b0 completed March 8, 2026, 4:19 p.m.
NED2 Entity disambiguation (via description) batch_69ada26804288190838a93b71b494650 completed March 8, 2026, 4:23 p.m.
Created at: March 4, 2026, 7:31 p.m.