Triple

T9931351
Position Surface form Disambiguated ID Type / Status
Subject MD5 E192654 entity
Predicate collisionResistance P11577 FINISHED
Object broken LITERAL 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: broken | Statement: [MD5, collisionResistance, broken]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: collisionResistance
Context triple: [MD5, collisionResistance, broken]
  • A. Merkle–Damgård strengthening
    Indicates that a hash function construction applies Merkle–Damgård strengthening, meaning the message is padded with its length (and possibly other structured padding) before processing to help ensure collision resistance and proper security properties.
  • B. notableResistance
    Indicates that an entity is recognized for having mounted a significant or distinguished opposition or defense against another entity or force.
  • C. cryptographicRelevance
    Indicates that something has significance, impact, or utility within a cryptographic context, such as for security, encryption, or cryptographic analysis.
  • D. cryptanalysisStatus chosen
    Indicates the current state or outcome of efforts to analyze or break a cryptographic system or cipher.
  • E. cryptographicModel
    Indicates a relationship where one entity serves as, or is based on, a particular cryptographic scheme, framework, or formal model.
  • F. None of above.

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.
PD Predicate disambiguation batch_69cd1d90b8a8819081748f129c0c6ab6 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:43 p.m.