Triple

T2633514
Position Surface form Disambiguated ID Type / Status
Subject B3 – Brasil Bolsa Balcão E59689 entity
Predicate alsoKnownAs P39 FINISHED
Object B3
B3 is Brazil’s main stock exchange, responsible for trading equities, derivatives, and other financial assets in the Brazilian market.
 E284203 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: B3 | Statement: [B3 – Brasil Bolsa Balcão, alsoKnownAs, B3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: B3
Context triple: [B3 – Brasil Bolsa Balcão, alsoKnownAs, B3]
  • 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. 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.
  • C. 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.
  • D. B
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • E. B
    B is an early systems programming language developed at Bell Labs that served as a direct precursor to the C programming language.
  • 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: B3
Triple: [B3 – Brasil Bolsa Balcão, alsoKnownAs, B3]
Generated description
B3 is Brazil’s main stock exchange, responsible for trading equities, derivatives, and other financial assets in the Brazilian market.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: B3
Target entity description: B3 is Brazil’s main stock exchange, responsible for trading equities, derivatives, and other financial assets in the Brazilian market.
  • 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. 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.
  • C. 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.
  • D. B
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • E. B
    B is an early systems programming language developed at Bell Labs that served as a direct precursor to the C programming language.
  • 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c8d32c819081fc89b91217ed54 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90a996188190b3a83a31e69d09ef completed March 10, 2026, 3:31 a.m.
NEDg Description generation batch_69af9172ba248190bbc68a00b43d9b44 completed March 10, 2026, 3:35 a.m.
NED2 Entity disambiguation (via description) batch_69af9253953c8190a8e18c92d66263cc completed March 10, 2026, 3:38 a.m.
Created at: March 6, 2026, 9:50 p.m.