Triple

T19063513
Position Surface form Disambiguated ID Type / Status
Subject Merkle proof E466595 entity
Predicate relatedTo P37 FINISHED
Object Merkle tree NE NERFINISHED

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: Merkle tree | Statement: [Merkle proof, relatedTo, Merkle tree]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Merkle tree
Context triple: [Merkle proof, relatedTo, Merkle tree]
  • A. Merkle tree chosen
    A Merkle tree is a cryptographic data structure that uses a tree of hash values to efficiently and securely verify the integrity and consistency of large sets of data.
  • B. Merkle
    Merkle is a surname most prominently associated with Ralph Merkle, a pioneering computer scientist and cryptographer known for his foundational work in public-key cryptography and Merkle trees.
  • C. Merkle Patricia tree
    A Merkle Patricia tree is a hybrid data structure combining Merkle trees and Patricia tries, widely used in systems like Ethereum to provide efficient, verifiable key–value storage.
  • D. Merkle proof
    A Merkle proof is a compact cryptographic proof that verifies a specific piece of data is included in a larger dataset by revealing only a minimal set of hash values from a Merkle tree.
  • E. Merkle–Damgård construction
    The Merkle–Damgård construction is a fundamental method for building collision-resistant cryptographic hash functions from fixed-size compression functions, used in many classic hash algorithms like MD5 and SHA-1.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd040fb881909af2a964f65ad208 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e196deac8190ad0406c616197e0b completed April 20, 2026, 8:19 a.m.
Created at: April 10, 2026, 12:03 p.m.