Triple

T4765334
Position Surface form Disambiguated ID Type / Status
Subject Byzantine Generals Problem E105795 entity
Predicate mainTopic P31 FINISHED
Object Byzantine fault tolerance
Byzantine fault tolerance is a property of distributed systems that enables them to reach correct consensus and continue operating reliably even when some components behave arbitrarily or maliciously.
E105795 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: Byzantine fault tolerance | Statement: [Byzantine Generals Problem, mainTopic, Byzantine fault tolerance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Byzantine fault tolerance
Context triple: [Byzantine Generals Problem, mainTopic, Byzantine fault tolerance]
  • A. Byzantine Generals Problem
    The Byzantine Generals Problem is a classic computer science and distributed systems thought experiment that illustrates the difficulty of achieving reliable consensus among participants in the presence of faulty or malicious actors.
  • B. "Reaching Agreement in the Presence of Faults"
    "Reaching Agreement in the Presence of Faults" is a seminal paper in distributed computing that introduced the Byzantine Generals Problem and laid the foundations for understanding consensus in unreliable, fault-prone systems.
  • C. Paxos consensus algorithm
    The Paxos consensus algorithm is a fault-tolerant protocol for achieving agreement among distributed systems, widely used as a foundation for reliable, replicated state machines and modern distributed databases.
  • D. Paxos
    Paxos is a small Greek island in the Ionian Sea, known for its clear turquoise waters, olive groves, and tranquil, less-touristed atmosphere.
  • E. "Time, Clocks, and the Ordering of Events in a Distributed System"
    "Time, Clocks, and the Ordering of Events in a Distributed System" is a seminal 1978 paper that introduced logical clocks and the happened-before relation, fundamentally shaping the theory and practice of distributed computing.
  • 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: Byzantine fault tolerance
Triple: [Byzantine Generals Problem, mainTopic, Byzantine fault tolerance]
Generated description
Byzantine fault tolerance is a property of distributed systems that enables them to reach correct consensus and continue operating reliably even when some components behave arbitrarily or maliciously.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Byzantine fault tolerance
Target entity description: Byzantine fault tolerance is a property of distributed systems that enables them to reach correct consensus and continue operating reliably even when some components behave arbitrarily or maliciously.
  • A. Byzantine Generals Problem chosen
    The Byzantine Generals Problem is a classic computer science and distributed systems thought experiment that illustrates the difficulty of achieving reliable consensus among participants in the presence of faulty or malicious actors.
  • B. "Reaching Agreement in the Presence of Faults"
    "Reaching Agreement in the Presence of Faults" is a seminal paper in distributed computing that introduced the Byzantine Generals Problem and laid the foundations for understanding consensus in unreliable, fault-prone systems.
  • C. Paxos consensus algorithm
    The Paxos consensus algorithm is a fault-tolerant protocol for achieving agreement among distributed systems, widely used as a foundation for reliable, replicated state machines and modern distributed databases.
  • D. Paxos
    Paxos is a small Greek island in the Ionian Sea, known for its clear turquoise waters, olive groves, and tranquil, less-touristed atmosphere.
  • E. "Time, Clocks, and the Ordering of Events in a Distributed System"
    "Time, Clocks, and the Ordering of Events in a Distributed System" is a seminal 1978 paper that introduced logical clocks and the happened-before relation, fundamentally shaping the theory and practice of distributed computing.
  • F. None of above.

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_69bd43f226fc8190b867cc249c2a9042 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd65327af48190881c25763232c368 completed March 20, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a87741081909380c51ba4efed92 completed March 21, 2026, 6:28 a.m.
NEDg Description generation batch_69be3d444b888190b2df7433502604ff completed March 21, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_69be3dd31c648190bfdac15fb85cfec9 completed March 21, 2026, 6:42 a.m.
Created at: March 20, 2026, 1:21 p.m.