Triple

T4765602
Position Surface form Disambiguated ID Type / Status
Subject Reaching Agreement in the Presence of Faults E105801 entity
Predicate relatedTo P37 FINISHED
Object Byzantine agreement problem E105795 NE FINISHED

How this triple was built (2 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 agreement problem | Statement: [Reaching Agreement in the Presence of Faults, relatedTo, Byzantine agreement problem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Byzantine agreement problem
Context triple: [Reaching Agreement in the Presence of Faults, relatedTo, Byzantine agreement problem]
  • A. Byzantine fault tolerance
    Byzantine fault tolerance is a property of distributed systems that enables them to continue operating correctly even when some components behave arbitrarily or maliciously.
  • B. 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.
  • C. "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.
  • D. Practical Byzantine Fault Tolerance
    Practical Byzantine Fault Tolerance is a consensus algorithm for distributed systems that efficiently tolerates Byzantine (arbitrary) faults, enabling reliable operation even when some nodes behave maliciously or unpredictably.
  • E. FLP impossibility result
    The FLP impossibility result is a foundational theorem in distributed computing showing that in an asynchronous system, no deterministic consensus protocol can guarantee both safety and liveness in the presence of even a single crash failure.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd6534d6b48190911c295b5601a762 completed March 20, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81a9d8f08190ac79ca210356aab4 completed March 21, 2026, 11:31 a.m.
Created at: March 20, 2026, 1:21 p.m.