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.