Triple
T15264342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Besu |
E364860
|
entity |
| Predicate | supportsConsensus |
P117864
|
FINISHED |
| Object |
Proof of Work
Proof of Work is a consensus mechanism in blockchain networks where participants solve computationally intensive puzzles to validate transactions and secure the ledger.
|
E1147451
|
NE FINISHED |
How this triple was built (5 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: Proof of Work | Statement: [Besu, supportsConsensus, Proof of Work]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Proof of Work Context triple: [Besu, supportsConsensus, Proof of Work]
-
A.
RPOW (Reusable Proofs of Work)
RPOW (Reusable Proofs of Work) was an early digital cash system proposed by Hal Finney that aimed to make proof-of-work tokens transferable and reusable, serving as a conceptual precursor to modern cryptocurrencies.
-
B.
Equihash
Equihash is a memory-hard, proof-of-work hashing algorithm designed to be ASIC-resistant and used in cryptocurrencies such as Zcash.
-
C.
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.
-
D.
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.
-
E.
Avalanche consensus
Avalanche consensus is a family of probabilistic, metastable consensus protocols that achieve high throughput and fast finality for decentralized networks through repeated randomized sampling and gossip-based voting.
- 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: Proof of Work Triple: [Besu, supportsConsensus, Proof of Work]
Generated description
Proof of Work is a consensus mechanism in blockchain networks where participants solve computationally intensive puzzles to validate transactions and secure the ledger.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Proof of Work Target entity description: Proof of Work is a consensus mechanism in blockchain networks where participants solve computationally intensive puzzles to validate transactions and secure the ledger.
-
A.
RPOW (Reusable Proofs of Work)
RPOW (Reusable Proofs of Work) was an early digital cash system proposed by Hal Finney that aimed to make proof-of-work tokens transferable and reusable, serving as a conceptual precursor to modern cryptocurrencies.
-
B.
Equihash
Equihash is a memory-hard, proof-of-work hashing algorithm designed to be ASIC-resistant and used in cryptocurrencies such as Zcash.
-
C.
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.
-
D.
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.
-
E.
Avalanche consensus
Avalanche consensus is a family of probabilistic, metastable consensus protocols that achieve high throughput and fast finality for decentralized networks through repeated randomized sampling and gossip-based voting.
- F. None of above. chosen
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsConsensus Context triple: [Besu, supportsConsensus, Proof of Work]
-
A.
adoptedByConsensus
Indicates that a decision, action, or change was formally accepted through a consensus process among the relevant participants.
-
B.
hasCurrentConsensus
Indicates that there is a presently agreed-upon or widely accepted position, judgment, or state regarding the related entities.
-
C.
notAdoptedByConsensus
Indicates that a proposal, decision, or action was not accepted or approved through a consensus-based process among the relevant parties.
-
D.
supportsBlockchain
Indicates that one entity provides compatibility with, infrastructure for, or endorsement of blockchain technology used by another entity.
-
E.
supportsRatificationOf
Indicates that one entity endorses or advocates for the formal approval or ratification of another entity (such as a treaty, agreement, or decision).
- F. None of above. chosen
Provenance (7 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. |
| PD | Predicate disambiguation | batch_69deca8d1bd48190a4b94f29b425e335 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2ca6148190967c319728ec3661 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:14 a.m.