Triple
T20259202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yiqun Lisa Yin |
E498785
|
entity |
| Predicate | coDesignerOf |
P184
|
FINISHED |
| Object | MD6 hash function |
—
|
NE NERFINISHED |
How this triple was built (3 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: MD6 hash function | Statement: [Yiqun Lisa Yin, coDesignerOf, MD6 hash function]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MD6 hash function Context triple: [Yiqun Lisa Yin, coDesignerOf, MD6 hash function]
-
A.
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.
-
B.
Whirlpool hash function
Whirlpool is a cryptographic hash function designed by Vincent Rijmen and Paulo S. L. M. Barreto, known for its wide-pipe construction and strong security properties suitable for digital signatures and data integrity.
-
C.
MD5
MD5 is a widely known but now cryptographically broken 128-bit hash function formerly used for checksums, data integrity, and security applications.
-
D.
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.
-
E.
Davies–Meyer compression function
The Davies–Meyer compression function is a classic construction in cryptography that builds a hash function’s compression step from a block cipher by feeding the cipher’s output back into the input via XOR.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MD6 hash function Target entity description: The MD6 hash function is a cryptographic hash algorithm proposed as a candidate for the SHA-3 standard, designed to provide strong security and efficient parallel performance.
-
A.
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.
-
B.
Whirlpool hash function
Whirlpool is a cryptographic hash function designed by Vincent Rijmen and Paulo S. L. M. Barreto, known for its wide-pipe construction and strong security properties suitable for digital signatures and data integrity.
-
C.
MD5
MD5 is a widely known but now cryptographically broken 128-bit hash function formerly used for checksums, data integrity, and security applications.
-
D.
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.
-
E.
Davies–Meyer compression function
The Davies–Meyer compression function is a classic construction in cryptography that builds a hash function’s compression step from a block cipher by feeding the cipher’s output back into the input via XOR.
- F. None of above. chosen
Provenance (2 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674c84e848190a6e8956698b84026 |
completed | April 20, 2026, 6:47 p.m. |
Created at: April 11, 2026, 11:41 p.m.