Triple

T9931373
Position Surface form Disambiguated ID Type / Status
Subject MD5 E192654 entity
Predicate replacedBy P101 FINISHED
Object SHA-3 E663897 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: SHA-3 | Statement: [MD5, replacedBy, SHA-3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SHA-3
Context triple: [MD5, replacedBy, SHA-3]
  • A. Keccak chosen
    Keccak is a cryptographic hash function family that forms the basis of the SHA-3 standard, known for its sponge construction and strong security properties.
  • B. SHA-2
    SHA-2 is a family of cryptographic hash functions widely used for data integrity, digital signatures, and security protocols on the internet.
  • C. SHA-256
    SHA-256 is a widely used cryptographic hash function from the SHA-2 family that produces a 256-bit hash value for securing data integrity and authentication.
  • D. Whirlpool hash function
    Whirlpool is a cryptographic hash function designed by Vincent Rijmen and Paulo S. L. M. Barreto, known for its wide-pipe construction and strong security properties suitable for digital signatures and data integrity.
  • 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 (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_69ca82dd978c8190947124ab0d3315ac completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5b54f348190b8e70e7beff6098a completed April 2, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d228cab0fc81908ff5fad6916c1bab completed April 5, 2026, 9:18 a.m.
Created at: March 30, 2026, 8:43 p.m.