Triple

T15264345
Position Surface form Disambiguated ID Type / Status
Subject Besu E364860 entity
Predicate supportsConsensus P117864 FINISHED
Object QBFT
QBFT is a Byzantine fault-tolerant consensus protocol used in blockchain networks to achieve reliable agreement among nodes even in the presence of faulty or malicious participants.
 E1147452 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: QBFT | Statement: [Besu, supportsConsensus, QBFT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: QBFT
Context triple: [Besu, supportsConsensus, QBFT]
  • A. FBFT
    FBFT is the ICAO airport code assigned to Francistown Airport in Botswana.
  • B. QFA
    QFA is the commonly used abbreviation for the Qatar Football Association, the governing body of football in Qatar.
  • C. QF
    QF is the IATA airline designator used for Qantas, the flag carrier of Australia.
  • D. QF
    QF is a "qualifying facility" under the U.S. Public Utility Regulatory Policies Act (PURPA), typically a small power producer or cogeneration plant that meets specific efficiency and fuel-use standards to receive certain regulatory benefits.
  • E. QVT
    QVT (Query/View/Transformation) is an OMG standard language for specifying model-to-model transformations in model-driven software engineering.
  • 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: QBFT
Triple: [Besu, supportsConsensus, QBFT]
Generated description
QBFT is a Byzantine fault-tolerant consensus protocol used in blockchain networks to achieve reliable agreement among nodes even in the presence of faulty or malicious participants.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: QBFT
Target entity description: QBFT is a Byzantine fault-tolerant consensus protocol used in blockchain networks to achieve reliable agreement among nodes even in the presence of faulty or malicious participants.
  • A. FBFT
    FBFT is the ICAO airport code assigned to Francistown Airport in Botswana.
  • B. QFA
    QFA is the commonly used abbreviation for the Qatar Football Association, the governing body of football in Qatar.
  • C. QF
    QF is the IATA airline designator used for Qantas, the flag carrier of Australia.
  • D. QF
    QF is a "qualifying facility" under the U.S. Public Utility Regulatory Policies Act (PURPA), typically a small power producer or cogeneration plant that meets specific efficiency and fuel-use standards to receive certain regulatory benefits.
  • E. QVT
    QVT (Query/View/Transformation) is an OMG standard language for specifying model-to-model transformations in model-driven software engineering.
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0084fed0481908e452c89cba2be82 completed April 15, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5fdc21881909d87062db6fb8fb7 completed May 9, 2026, 7:45 a.m.
NEDg Description generation batch_69fee714cf6c81908dc4427590eeae85 completed May 9, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69feeae4731081909964bd8b1ea3dd7a completed May 9, 2026, 8:05 a.m.
Created at: April 10, 2026, 3:14 a.m.