Triple

T12515736
Position Surface form Disambiguated ID Type / Status
Subject RIPEMD-160 E299186 entity
Predicate predecessor P97 FINISHED
Object RIPEMD E986988 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: RIPEMD | Statement: [RIPEMD-160, predecessor, RIPEMD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RIPEMD
Context triple: [RIPEMD-160, predecessor, RIPEMD]
  • A. RIPEMD chosen
    RIPEMD is a family of cryptographic hash functions designed as an alternative to MD4 and MD5, known for variants like RIPEMD-160 used in security and blockchain applications.
  • B. RIPEMD-160
    RIPEMD-160 is a 160-bit cryptographic hash function designed as an alternative to SHA-1, commonly used for data integrity and security applications.
  • C. SHA-1
    SHA-1 is a now-legacy 160-bit cryptographic hash function once widely used for data integrity and digital signatures but today considered insecure due to practical collision attacks.
  • D. MD4
    MD4 is a cryptographic hash function designed by Ronald Rivest that produces a 128-bit hash value and served as the basis for later algorithms like MD5.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541f80148190976d1d912fe155d0 completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65eac74608190a6f1941ed5a05212 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 9:57 p.m.