Triple
T37150019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avalanche consensus |
E920337
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Byzantine fault tolerant consensus protocol |
C41036
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: Byzantine fault tolerant consensus protocol Context triple: [Avalanche consensus, instanceOf, Byzantine fault tolerant consensus protocol]
-
A.
fault-tolerant consensus protocol
chosen
A fault-tolerant consensus protocol is a distributed algorithm that enables a group of nodes to reliably agree on a shared state or value even when some nodes fail or behave maliciously.
-
B.
distributed consensus algorithm
A distributed consensus algorithm is a protocol that enables a group of independent, networked nodes to reliably agree on a single shared value or state, even in the presence of failures or unreliable communication.
-
C.
theorem in distributed computing
A theorem in distributed computing is a formally proven statement that characterizes fundamental limits, guarantees, or behaviors of distributed systems under specified models, assumptions, and failure conditions.
-
D.
Algorand protocol feature
An Algorand protocol feature is a specific built-in capability or mechanism of the Algorand blockchain that enhances its security, scalability, consensus, or smart contract functionality.
-
E.
proof-of-work system
A proof-of-work system is a consensus mechanism in which participants must perform and verifiably demonstrate computationally expensive work to gain the right to add new records or blocks, thereby securing the system against abuse.
- F. None of above.
Provenance (1 batch)
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_69f76e9f87c08190b4c8f7fafbd8345a |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:15 p.m.