Triple

T2836203
Position Surface form Disambiguated ID Type / Status
Subject B13 federal road E62356 entity
Predicate abbreviation P43 FINISHED
Object B 13
B 13 is a German federal highway (Bundesstraße) that runs north–south through several regions, connecting major towns and cities.
 E303467 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: B 13 | Statement: [B13 federal road, abbreviation, B 13]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: B 13
Context triple: [B13 federal road, abbreviation, B 13]
  • A. B3
    B3 is the third-generation Volkswagen Passat, produced in the early 1990s and known for its aerodynamic, grille-less front design and improved engineering over its predecessors.
  • B. B3
    B3 is Brazil’s main stock exchange, responsible for trading equities, derivatives, and other financial assets in the Brazilian market.
  • C. B
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • D. B
    B is an early systems programming language developed at Bell Labs that served as a direct precursor to the C programming language.
  • E. 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.
  • 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: B 13
Triple: [B13 federal road, abbreviation, B 13]
Generated description
B 13 is a German federal highway (Bundesstraße) that runs north–south through several regions, connecting major towns and cities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: B 13
Target entity description: B 13 is a German federal highway (Bundesstraße) that runs north–south through several regions, connecting major towns and cities.
  • A. B3
    B3 is the third-generation Volkswagen Passat, produced in the early 1990s and known for its aerodynamic, grille-less front design and improved engineering over its predecessors.
  • B. B3
    B3 is Brazil’s main stock exchange, responsible for trading equities, derivatives, and other financial assets in the Brazilian market.
  • C. B
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • D. B
    B is an early systems programming language developed at Bell Labs that served as a direct precursor to the C programming language.
  • E. 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.
  • 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_69ab4c3c39188190955b9c49d98463d8 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdeec60a08190b76b52042713d647 completed March 7, 2026, 8:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8c890508190868f50f4e5e1d642 completed March 10, 2026, 9:47 a.m.
NEDg Description generation batch_69afe9ba068881908727c82d5eddb974 completed March 10, 2026, 9:51 a.m.
NED2 Entity disambiguation (via description) batch_69b00412e7448190898050f18f64ea9a completed March 10, 2026, 11:44 a.m.
Created at: March 6, 2026, 10:01 p.m.