Triple
T4381643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merkle–Damgård construction |
E99142
|
entity |
| Predicate | usedIn |
P98
|
FINISHED |
| Object | RIPEMD-160 |
E299186
|
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: RIPEMD-160 | Statement: [Merkle–Damgård construction, usedIn, RIPEMD-160]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RIPEMD-160 Context triple: [Merkle–Damgård construction, usedIn, RIPEMD-160]
-
A.
RIPEMD-160
chosen
RIPEMD-160 is a 160-bit cryptographic hash function designed as an alternative to SHA-1, commonly used for data integrity and security applications.
-
B.
SHA-256
SHA-256 is a widely used cryptographic hash function from the SHA-2 family that produces a 256-bit hash value for securing data integrity and authentication.
-
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.
CRAM-MD5
CRAM-MD5 is a challenge–response authentication mechanism that uses MD5 hashing to securely verify a user's identity without transmitting their password in plaintext.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352613dd481909e008a8db239a108 |
completed | March 12, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e51ff9188190aa4581d451feaafd |
completed | March 14, 2026, 10:45 p.m. |
Created at: March 12, 2026, 11:18 p.m.