Triple

T2002192
Position Surface form Disambiguated ID Type / Status
Subject Daniel J. Bernstein E43494 entity
Predicate thesisTitle P1860 FINISHED
Object Computing short vectors in lattices
"Computing short vectors in lattices" is Daniel J. Bernstein's doctoral thesis, focusing on algorithms and complexity issues related to finding short vectors in mathematical lattices, a central problem in computational number theory and cryptography.
E224030 NE FINISHED

How this triple was built (4 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: Computing short vectors in lattices | Statement: [Daniel J. Bernstein, thesisTitle, Computing short vectors in lattices]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Computing short vectors in lattices
Context triple: [Daniel J. Bernstein, thesisTitle, Computing short vectors in lattices]
  • A. Shamir’s attack on RSA with low decryption exponent
    Shamir’s attack on RSA with low decryption exponent is a cryptanalytic method that exploits unusually small private exponents in RSA to efficiently recover the secret key and break the encryption.
  • B. Blum–Blum–Shub pseudorandom number generator
    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.
  • C. 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.
  • D. Håstad’s switching lemma
    Håstad’s switching lemma is a fundamental result in computational complexity theory that provides powerful bounds on the simplification of Boolean formulas under random restrictions, with major applications in circuit lower bounds.
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Computing short vectors in lattices
Triple: [Daniel J. Bernstein, thesisTitle, Computing short vectors in lattices]
Generated description
"Computing short vectors in lattices" is Daniel J. Bernstein's doctoral thesis, focusing on algorithms and complexity issues related to finding short vectors in mathematical lattices, a central problem in computational number theory and cryptography.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Computing short vectors in lattices
Target entity description: "Computing short vectors in lattices" is Daniel J. Bernstein's doctoral thesis, focusing on algorithms and complexity issues related to finding short vectors in mathematical lattices, a central problem in computational number theory and cryptography.
  • A. Shamir’s attack on RSA with low decryption exponent
    Shamir’s attack on RSA with low decryption exponent is a cryptanalytic method that exploits unusually small private exponents in RSA to efficiently recover the secret key and break the encryption.
  • B. Blum–Blum–Shub pseudorandom number generator
    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.
  • C. 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.
  • D. Håstad’s switching lemma
    Håstad’s switching lemma is a fundamental result in computational complexity theory that provides powerful bounds on the simplification of Boolean formulas under random restrictions, with major applications in circuit lower bounds.
  • E. 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.
  • F. None of above. chosen

Provenance (5 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_69a88715dbbc8190b2299e29e955d997 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8820cec8190a945e5daeb8c9df6 completed March 7, 2026, 5:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0342ef8c8190b7771076282981c3 completed March 8, 2026, 11:16 p.m.
NEDg Description generation batch_69ae057cc1a08190895031fa6c095f49 completed March 8, 2026, 11:25 p.m.
NED2 Entity disambiguation (via description) batch_69ae0751eff4819086e5469a2c56a24d completed March 8, 2026, 11:33 p.m.
Created at: March 4, 2026, 7:37 p.m.