Triple

T5214020
Position Surface form Disambiguated ID Type / Status
Subject Blum–Micali pseudorandom number generator E117703 entity
Predicate relatedTo P37 FINISHED
Object Blum–Blum–Shub pseudorandom number generator E118448 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: Blum–Blum–Shub pseudorandom number generator | Statement: [Blum–Micali pseudorandom number generator, relatedTo, Blum–Blum–Shub pseudorandom number generator]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blum–Blum–Shub pseudorandom number generator
Context triple: [Blum–Micali pseudorandom number generator, relatedTo, Blum–Blum–Shub pseudorandom number generator]
  • A. Blum–Blum–Shub pseudorandom number generator chosen
    The Blum–Blum–Shub pseudorandom number generator is a cryptographically secure generator based on the hardness of factoring large composite numbers, widely studied in theoretical computer science and cryptography.
  • B. Blum–Micali pseudorandom number generator
    The Blum–Micali pseudorandom number generator is a foundational cryptographic algorithm that produces provably secure pseudorandom bits based on number-theoretic hardness assumptions.
  • C. Merkle–Hellman knapsack cryptosystem
    The Merkle–Hellman knapsack cryptosystem is an early public-key encryption scheme based on the subset sum (knapsack) problem, historically significant as one of the first practical public-key systems though later found to be insecure.
  • D. Probabilistic Encryption
    Probabilistic Encryption is a cryptographic technique that uses randomness in the encryption process so that the same message encrypts to different ciphertexts, enhancing security against attackers.
  • E. Modern Cryptography, Probabilistic Proofs and Pseudorandomness
    "Modern Cryptography, Probabilistic Proofs and Pseudorandomness" is a foundational textbook that systematically develops the theoretical underpinnings of modern cryptography, focusing on probabilistic proof techniques and the theory of pseudorandomness.
  • 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_69bd4464ba3c8190bc16b2ebbe42ddb0 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a911d40819086621537274dc0f0 completed March 20, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefe325988190b35e3502f147c9c2 completed March 21, 2026, 7:22 p.m.
Created at: March 20, 2026, 1:47 p.m.